ML061070632

Units 1, 2, & 3 - GENE-0000-0052-3661-01-NP, Test Report #1, Browns Ferry Nuclear Plant; Unit 1, Scale Model Test.

ML061070632
Person / Time
Site:	Browns Ferry
Issue date:	04/30/2006
From:	General Electric Co
To:	Office of Nuclear Reactor Regulation
References
DRF 0000-0045-0918, TVA-BFN-TS-418, TVA-BFN-TS-431 GENE-0000-0052-3661-01-NP
Download: ML061070632 (230)

Text

ENCLOSURE 2 TENNESSEE VALLEY AUTHORITY BROWNS FERRY NUCLEAR PLANT (BFN)

UNITS 1, 2, AND 3 TECHNICAL SPECIFICATIONS (TS) CHANGE NOS. TS-418 AND TS-431 -

REQUEST FOR EXTENDED POWER UPRATE (EPU) OPERATION -

STEAM DRYER SCALE MODEL TEST REPORT (NON-PROPRIETARY VERSION)

Attached is the Non-Proprietary Version of GENE-0000-0052-3661-01, Test Report # 1, Browns Ferry Nuclear Plant, Unit 1, Scale Model Test."

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP GE Nuclear Eneiqy 1989 Little Orchard Street San Jose, CA 95125 GENE-0000-0052-366 1-01-NP DRF 0000-0045-0918 Class I April 2006 Test Report # I Browns Ferry Nuclear Plant, Unit 1 Scale Model Test

-_1 NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01-NP IMPORTANT NOTICE REGARDING TIlE CONTENTS OF TIllS REPORT Please Read Carefully The only undertakings of the General Electric Company (GENE) with respect to the information in this document are contained in the contract between TVA and GENE, and nothing contained in this document shall be construed as changing the contract. The use of' this information by anyone other than TVA or for any purpose other than that for which it is intended, is not authorized; and with respect to any unauthorized use, GENE makes no representation or warranty, express or implied, and assumes no liability as to the completeness, accuracy, or usefulness of the information contained in this document, or that its use may not infringe upon privately owned rights.

IMPORTANT NOTICE This is a non-proprietary version of the document GE-NE-0000-0052-3661-01-P, which hE.s the proprietary information removed. Portions of the document that have been removed are indicated by an open and closed double brackets as shown here (( )).

Page i of xii

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Table of Contents 1.0 Executive Summary ..................................................... 1 2.0 Scope ..................................................... 3 3.0 Description of Test Apparatus ................ ..................................... 4 3.1 BWR Scale Test Apparatus .............................................................. 4 3.2 BWR Model Acoustic Test Fixture .............................................................. 6 3.3 Browns Ferry Nuclear Plant Unit I Plant Specific Scale Model ............. .............. 7 3.4 Model Components used for Sensitivity Testing .................................................. 12 3.5 Scale Modeling Assumptions and Approximations ............................................. 15 4.0 Scaling Factors used to convert Model data to Plant Scale ........................ 30 5.0 Data Acquisition System and Instnimentation .............................................. 32 5.1 Sensor Locations ............................................................. 34 6.0 Test Matrix .................................................... 48 6.1 Characterization Testing ............................................................. 48 6.2 Sensitivity Testing ............................................................. 50 6.2.1 Blind Flange/ Main Steam Relief Valve Sensitivity Tests ................................ 51 6.2.2 Main Steam Line Length Sensitivity Tests ....................................................... 52 6.2.3 Turbine Control and Turbine Stop Valve Sensitivity Tests .............................. 53 6.3 Baseline Testing ............................................................. 53 7.0 Data Analysis Methods .................................................... 56 7.1.1 Data Acquisition ............................................................. 56 7.1.2 Data Processing ............................................................. 57 7.1.2.1 Peak Hold Autopower Spectra ............................................................. 58 7.1.2.2 Peak Hold Autopower Spectra Scaled to Plant Scale ................. ................... 58 7.1.2.3 Linear Average Autopower Spectra ............................................................. 59 7.1.2.4 Linear Average Autopower Spectra Scaled to Plant Scale ............. ............... 59 7.1.2.5 Linear Average Crosspower Spectra ............................................................. 60 7.1.2.6 RMS Level of Frequency Band versus time and flow ................ ................... 61 8.0 Presentation of Results .................................................... 62 8.1 Sensitivity Testing ............................................................. 62 8.1.1 Blind Flange and Main Steam Relief Valve Sensitivity Tests ............ .............. 62 8.1.2 Main Steam Line Length Sensitivity Tests ....................................................... 66 S.1.3 Effect of Geometrically Detailed Turbine Stop Valves/Turbine Control Valves 77 8.2 Baseline Testing .......................................................... 82 8.2.1 Steady State Results .......................................................... 82 8.2.2 Comparisons to Previous Data .......................................................... 97 8.2.3 Flow Sweep Test Results ............................ 104 8.2.4 Operating Pressure Shapes ............................ 115 9.0 Uncertainty Analysis ............................ 126 1(0.0 Data used for Load Definition ........................ 128 10.1 Process for Selection of Segment ............................ 128 10.2 Review of Results ............................ 129 Page ii of xii

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 10.3 BFNI SMT Load Definition Process ................................................... 137 10.4 Frequency-Specific Weighting Results for LIA Segment................................ 140 11.0 Discussion and Conclusions ........................................... 147 1:2.0 References ........................................... 149 Appendix A: Dryer Autopower Spectra at EPU - LIA Input ......................... 150 Appendix B: Dryer Autopower Spectra at EPU - ACM Input ...................... 161 Appendix C: Dryer Autopower Spectra at OLTP - LIA Input ...................... 176 Appendix D: Dryer Autopower Spectra at OLTP - ACM Input ................... 187 Appendix E: Dryer Autopower Spectra during Sweep .................................... 202 Page iii of xii

NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01 -NP List of Tables Table 1: Calculated Frequencies of MSRV and Blind Flange Standpipes ........... ........... 23 Table 2a: Channel List for Initial Run with Vessel Mics only - used for LIA Input ...... 44 Table 2b: Remainder of Channel List for Initial Run with Vessel Mics only - used for LIA Input.................................................................................................................... 45 Table 3a: Channel List for Initial Run with MSL microphones - used for ACM Input.. 46 Table 3b: Remainder of Channel List for Initial Run with MSL microphones - used for ACM Input ............................................................. 47 Table 4: Standpipe Lengths ............................................................. 51 Table 5a: RMS Level Results from Frequency Bands for MSL A Length Sensitivity ... 75 Table 5b: RMS Level Results from Frequency Bands for MSL B Length Sensitivity ... 75 Table 5c: RMS Level Results from Frequency Bands for MSL C Length Sensitivity .... 76 Table 5d: RMS Level Results from Frequency Bands for MSL D Length Sensitivity ... 76 Table 6: RMS Level for (( )) Band (Model Scale) for Simple TSV/TCV and Geometrically Detailed TSV/TCV .................................................... 77 List of Figures Figure 1: General schematic of GE BWR Model Acoustic test apparatus with the BFN I scale model attached 5 Figure 2: Digital photograph of the GE BWR Model Acoustic test apparatus with the BFNI scale model attached 5 Figure 3: Schematic of the BWR Model Acoustic Test Fixture 7 Figure 4: Digital photograph of the BFNI RPV cylinder and top head. 8 Figure 5: Digital photographs of the BFNI model steam dryer 9 Figure 6: Schematic of the BFNI model main steam system. 10 Figure 7: Picture of the BFNI Scale Model Piping System 11 Figure 8: Picture of the BFNI Scale Model Vessel and Piping System 11 Figure 9: Picture of the BFNI Scale Model Vessel and Piping System 12 Figure 10: Schematic of the BF/MSRV length adjuster 13 Figure 11: Picture of the BF/MSRV length adjusters as installed 14 Figure 12: Schematic of the MSL length adjusters 15 Figure 13: Schematic of separator plate installed in the model steam dryer 18 Figure 14: Picture of(( )) simulating steam separator outlet as installed in BFNI scale model 18 Figure 15: Picture of Perforated Plates simulating vane banks as installed in BFN I scale model 20 Figure 16: Additional Detail of Perforated Plates simulating vane banks in BFNI scale model. 21 Figure 17: Schematic of the MSIV scale valve body 24 Figure 18: Picture of the MSIV scale valve bodies as installed on the scale model test rig 24 Figure 19: Schematic of the scale Turbine Control Valve 26 Page iv of xii

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 20: Schematic of the scale Turbine Stop Valve 27 Figure 21: Picture of the TCV/TSV Assembly 27 Figure 22: Picture of the simplified TCVITSV Assembly 27 Figure 23: Block Diagram of Data Acquisition and Blower Control System 33 Figure 24: Picture of the O° Side with Sensor Locations 36 Figure 25: Picture of the 900 Side with Sensor Locations 37 Figure 26: Picture of the 180°Side with Sensor Locations 38 Figure 27: Picture of the 270° Side with Sensor Locations 39 Figure 28: Picture of the Dryer Top with Sensor Locations 40 Figure 29: Schematic of the Vessel with Sensor Locations 41 Figure 30: Schematic of the MSL Sensor Locations (microphones in scale model, strain gages at plant) 42 Figure 31: Picture of the MSL C/D side of Vessel with Sensor Locations and with MSL C and D Sensor Locations 43 Figure 32: Picture of the MSL C/D side with MSL C and D Sensor Locations Highlighted in Yellow 43 Figure 33: Model configuration for characterization testing. 50 Figure 34: Schematic of model configuration used for MSL length sensitivity tests. 53 Figure 35: Comparison of Response at Dryer Location M:2 with Nominal Valve Settings (Green) and Adjusted Valve Settings (Red) at EPU. 64 Figure 36: Comparison of Response at Dryer Location M:3 with Nominal Valve Settings (Green) and Adjusted Valve Settings (Red) at EPU. 64 Figure 37: Comparison of Response at Dryer Location M:9 with Nominal Valve Settings (Green) and Adjusted Valve Settings (Red) at EPU. 65 Figure 38: Comparison of Response at Dryer Location M:10 with Nominal Vtive Settings (Green) and Adjusted Valve Settings (Red) at EPU. 65 Figure 39: Comparison of Response at Dryer Location M:2 with Nominal Valve Settings (Green) and No D-Ring (Red) at EPU. 68 Figure 40: Comparison of Response at Dryer Location M:10 with Nominal Valve Settings (Green) and No D-Ring (Red) at EPU. 69 Figure 41: Autopowers Acquired During MSL A Length Sensitivity Study at EPU. 70 Figure 42: RMS Level and Peak Amplitude for (( )) Hz Peak During MSL A Length Sensitivity Study at EPU. 71 Figure 43: RMS Level and Peak Amplitude for (( )) Hz Peak During MSL B Length Sensitivity Study at EPU. 72 Figure 44: RMS Level and Peak Amplitude for (( )) Hz Peak During MSL C Length Sensitivity Study at EPU. 73 Figure 45: RMS Level and Peak Amplitude for (( )) Hz Peak During MSL D Length Sensitivity Study at EPU. 74 Figure 46: Comparison of Response at Dryer Location M:2 with Geometrically Detailed TSV/TCVs (Green) and Simple TSV/TCVs (Red) at EPU. 78 Figure 47: Comparison of Response at Dryer Location M:4 with Geometrically Detailed TSV/TCVs (Green) and Simple TSV/TCN's (Red) at EPU. 79 Figure 48: Comparison of Response at DryerLocation M:10 with Geometrically Detailed TSV/TCVs (Green) and Simple TSV/TfCVs (Red) at EPU. 80 Page v of xii

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 49: Comparison of Response at Dryer Location M:15 with Geometrically Detailed TSV/TCVs (Green) and Simple TSV/TCVs (Red) at EPU. 81 Figure 50: EPU (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor M:2, 2700 Outer Hood Lower Corner 84 Figure 51: EPU (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor M:9, 270° Outer Hood Upper Corner 85 Figure 52: EPU (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor M:17, 270° Inner Hood 86 Figure 53: EPU (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor M:7, 1800 Skirt 87 Figure 54: EPU (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor M:4, 2700 Skirt 88 Figure 55: EPU (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor MSL C: I, Main Steam Line C 89 Figure 56: Comparison of Dryer Interior and Dryer Exterior Response at Lower Corner of Outer Hood, 2700 Face, Dryer Locations M:2, Exterior (Green) and M:I, Interior (Red) at EPU. 90 Figure 57: Comparison of Dryer Interior and Dryer Exterior Response at Skirt, 270° Face, Dryer Locations M:4, Exterior (Green) and M:5, Interior (Red) at EPU. 91 Figure 58: Comparison of Dryer Interior and Dryer Exterior Response at Skirt, 1800 Face, Dryer Locations M:7, Exterior (Green) and M:8, Interior (Red) at EPU. 92 Figure 59: Comparison of MSL, Dryer Outer Hood, and Interior of Dryer Outer Hood Responses 2700 Face: MSL C:1, MSL (Red), M:2, Outer Hood (Green), and M:1, Interior of Outer Hood (Blue) at EPU (converted to plant scale) 94 Figure 60: Comparison of MSL, Dryer Outer Hood, Dryer Inner Hood and Dryer Interior Responses at 90° Face: MSL A:1, MSL (Red), M:10, Outer Hood (Green), M:17, Inner Hood (Blue), and M:11, Interior of Outer Hood (Pink) at EPU (converted to plant scale). 95 Figure 61: Comparison of MSL, Dryer Skirt Exterior, and Dryer Skirt Interior Responses at 1800 Face: MSL C:1, MSL (Red), M:4, Skirt Exterior (Green), and M:5, Skirt Interior (Blue) at EPU (converted to plant scale) 96 Figure 62: Comparison of Response at Upper Corners of Dryer Outer Hood, Red-QC2 Plant, Green - QC2 SMT, Blue - BFNI SMT 2700 Face, Pink BFNI SMT 900 Face at EPU. 98 Figure 63: Comparison of Response on Dryer Skirt, Red - QC2 Plant, Green - QC2 SMT, Blue - BFNI 2700 Face, Pink BFN1 SMT 900 Face at EPU. 99 Figure 64: Comparison of Response at Lower Corners of Dryer Outer Hood, Red - QC2 Plant, Green - QC2 SMT, Blue - BFNI SMT 2700 Face, Pink BFNI SMT 900 Face at EPU. 100 Figure 65: Comparison of Response at Lower Comers of Dryer Outer Hood, Red - QC2 Plant, Green - QC2 SMT, Blue - BFNI SMT 2700 Face, Pink BFNI SMT 900 Face at EPU. 101 Figure 66: Comparison of Response at Inner Hood, Red - QC2 Plant, Green - QC2 SMT, Blue - BFNI SMT at EPU. 102 Figure 67: Comparison of Response at Inner Hood, Red - QC2 Plant, Green - QC2 SMT, Blue- .BFN1 SMT at EPU. 103 Page vi of xii

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01 -NP Figure 68: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:3, White Dashed line is OLTP, Yellow Dashed line is EPU 106 Figure 69: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:9, White Dashed line is OLTP, Yellow Dashed line is EPU 107 Figure 70: Curve Fits of Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, (( )) Band 10s Figure 71: Curve Fits of Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, (( )) Band 109 Figure 72: Curve Fits of Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, (( )) Band 110 Figure 73: Curve Fits of Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, (( )) Band 111 Figure 74: Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, (( )) Band 112 Figure 75: Curve Fits of Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, Sensor M: 10 for (( )) Band 113 Figure 76: Fluctuating Pressure Frequency Band versus Strouhal number for Dryer Outer Hood, Sensor M:10 for (( )) Band 114 Figure 77: Summed Crosspower Spectra of Whole Time Record for LIA input (Green) and Whole Time Record for ACM input (Red) at EPU. 116 Figure 78: Undeformed Shape of Vessel. Red Wireframe Remains Undeformed. 117 Figure 79: Static Depiction of (( )) Operating Pressure Shape at EPU (Note: Red Wireframe remains undeformed) 118 Figure 80: Static Depiction of(( )) Operating Pressure Shape at EPU, Opposite Phase from Previous 119 Figure 81: Static Depiction of (( )) Operating Pressure Shape at EPU 120 Figure 82: Static Depiction of ((

f] Operating Pressure Shape at EPU, Opposite Phase from Previous 121 Figure 83: Static Depiction of(( )) Operating Pressure Shape at EPU 122 Figure 84: Static Depiction of(( )) Operating Pressure Shape at EPU, Opposite Phase from above 123 Figure 85: Static Depiction of(( )) Operating Pressure Shape at EPU, 124 Figure 86: Static Depiction of(( )) Operating Pressure Shape at EPU, Opposite Phase from above 125 Figure 87: LIA Input Comparison of Representative Segment (Green - 26.8 to 27.0 Seconds) - to Whole Time Record (Red) for transducer M:2 at EPU. Upper -

Linear Average; Lower - Peak Hold Average 131 Figure 88: LIA Input Comparison of Representative Segment (Green - 26.8 to 27.0 Seconds) - to Whole Time Record (Red) for transducer M:9 at EPU. Upper -

Linear Average; Lower -Peak Hold Average 131 Figure 89: ACM Input Comparison of Representative Segment (Green - 11.41 to 11.61 Seconds) - to Whole Time Record (Red) for transducer M:3 at EPU. Upper

- Linear Average; Lower - Peak Hold Average 132 Page vii of xii

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 90: ACM Input Comparison of Representative Segment (Green - 11.41 to 11.61 Seconds) - to Whole Time Record (Red) for transducer M: 10 at EPU. Upper

- Linear Average; Lower - Peak Hold Average 132 Figure 91: ACM (Red) versus LIA (Green) Input Comparison for transducer M:7 at OLTP. Upper - Linear Average; Lower - Peak Hold Average 134 Figure 92: ACMI (Red) versus LIA (Green) Input Comparison for transducer M:10 at OLTP. Upper - Linear Average; Lower - Peak Hold Average 135 Figure 93: ACM (Red) versus LIA (Green) Input Comparison for transducer M:2 at EPU. Upper - Linear Average; Lower - Peak Hold Average 135 Figure 94: ACM (Red) versus LIA (Green) Input Comparison for transducer M:9 at EPU. Upper- Linear Average; Lower - Peak Hold Average 136 Figure 95: ACM (Red) versus LIA (Green) Input Comparison for transducer M:9 at EPU for whole record. Linear Average Results. 136 Figure 96: Filter Characteristic for Frequency Specific Weighting of Input to LIA - EPU (Red) and OLTP (Green) (Frequency Difference accounted for in Frequency scaling) 142 Figure 97: Comparison of Autopowers used as LIA Input after (Green) and before (Red) Frequency-Specific Weighting for Sensor M:2 at EPU 143 Figure 98: Comparison of Time Records used as LIA Input after (Green) and before (Red) Frequency-Specific Weighting for Sensor M:2 at EPU 144 Figure 99: Comparison of Autopowers used as LIA Input after (Green) and before (Red) Frequency-Specific Weighting for Sensor M:9 at EPU 145 Figure 100: Comparison of Time Records used as LIA Input after (Green) and before (Red) Frequency-Specific Weighting for Sensor M:9 at EPU 146 Page viii of xii

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Acronyms ACM ....................................... Acoustic Circuit Model BF ....................................... Blind Flange Browns Ferry Nuclear Plant, BFN 1 .......................................

Unit I BWR ....................................... Boiling Water Reactor CFM ....................................... Cubic Feet per Minute CL ....................................... centerline DAS ....................................... Data Acquisition System EMA ....................................... Experimental Modal Analysis EPU ....................................... Extended Power Uprate FDM ....................................... Fused Deposition Modeling FEM ....................................... Finite Element Model FRF ....................................... Frequency Response Function GE ....................................... General Electric GENE ....................................... General Electric Nuclear Energy HPCI ....................................... High Pressure Coolant Injection ID ....................................... Inside Diameter Page ix of xii

-_1 NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Acronyms, cont.

LIA Load Interpolation Algorithm LMS ....................................... Leuven Measurement Systems Mid Frequency Volume MFVVS ....................................... Velocity Source MS ....................................... Main Steam MSL ....................................... Main Steam Line MSIV ....................................... Main Steam Isolation Valve ODS ....................................... Operational Deflection Shape Original Licensed Thermal OLTP .......................................

Power PC ....................................... Personal Computer QC ....................................... Quad Cities RAM ....................................... Random Access Memory RCIC ....................................... Reactor Core Isolation Cooling RMS, rms ....................................... Root Mean Square RPV ....................................... Reactor Pressure Vessel RV ....................................... Relief Valve S/RV ....................................... Safety Relief Valve Page x of xii

NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01-NP Acronyms, cont.

SLA ....................................... Stereolithography SMT ....................................... Scale Model Test St ....................................... Strouhal Number SV Safety Valve TCV Turbine Control Valve Test Specification and TS&P Procedure TSV Turbine Stop Valve TVA Tennessee Valley Authority VNC Vallecitos Nuclear Center VPF Vane Passing Frequency Page xi of xii

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Nomenclature Sound Speed in air (

Cnl fI's

• -100 'F, 14.7 psia CP Sound Speed in steam @ .fl/v

-540 0 F, 1050 psia Flow Coefficient for gal CV .......................................

valves min. 1,si 2 F ....................................... SCADAS Scaling Factor I'a'nl' Model frequency fm ....................................... Hz (test data) fp ....................................... Plant frequency (test data)

G ....................................... Preamplifier gain Diwenisionle.ss K ....................................... Resistance Coefficient Dinlei'sionless Pml ....................................... Model pressure (test data) psi Pp ....................................... Plant pressure (test data) psi Volumetric flow rate in QEPU the model equivalent to CFM EPU in the plant Volumetric flow rate in QOI.Ti' the model equivalent to CFM OLTP in the plant S ....................................... Microphone sensitivity ntmV/Pa St ....................................... Strouhal Number Dimnerisionless Percentage uncertainty lI%(X) ....................................... Dieire.sionless associated with variable x Vill ....................................... Air velocity in the model fl/s VP Steam velocity in the plant ft/s Page xii of xii

NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01-NP 1.0 Executive Summary A series of scale model tests of the Browns Ferry Nuclear Plant, Unit I (BFNI) configuration were performed using a scale model testing apparatus and methodology.

The purpose of these tests was to obtain data that could be used to create a predictive Extended Power Uprate (EPU) steam dryer normal operation fluctuating load definition.

These tests consisted of both sweep tests from below Original Licensed Thermal Power (C)LTP) to beyond EPU conditions and dwell tests at several flow rates in the range of interest. Ten microphones were attached to the outside surface of the steam dryer, two microphones were attached to the dryer bank panels, six microphones were attached to the inside surface of the steam dryer, and eight microphones were attached to the main steam lines. Fifty-three microphones were used to cover ninety-two locations on the interior wall of the pressure vessel. Using the appropriate scaling relationships, model frequencies and amplitudes can be scaled to plant conditions by dividing the frequency by approximately (( )) and multiplying the pressure by approximately (( ))

The scaling factors are a function of test fluid temperature and density; therefore, the exact value will vary depending on the actual fluid temperature and mean pressure measured during each test run. When these factors are calculated for a specific test, exact amplitude and frequency.scaling values are generated for that condition based on the specific temperatures and pressures at that condition.

Substantial information was obtained from the baseline and sensitivity tests performed on the BFNI plant configuration. The following conclusions and observations were made:

• The BFN I SMT data show the same general characteristics of BWR steam dryer fluctuating pressure loads that were described in the GE SMT Benchmark report

[I]

• The BFNI SMT data predict the presence of a (( )) at BFNI that exhibits (( ))

• The amplitude of the (( )) in the BFN1 SMT data is lower than both the QC2 plant and the QC2 SMT data.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP

• The BFNl inner hoods show little influence from the (( ]

The BFNl SMT trends of fluctuating pressure versus flow for the four frequency bands considered to be important in the BWR main steam system are similar to results found for other plant tests and other model tests as provided in Reference I o The (( )) signal increases in amplitude versus flow with a power law exponent of approximately (( ff in the OLTP/EPU range; however, it appears to (( )) The trend exhibited by this signal as well as the ((

o Frequency ranges excluding the (( )) signal increase in amplitude versus flow with a power law exponent of approximately f(( ] In other words, the amplitude increase is proportional to flow velocity

(( )) which is consistent with a mechanism.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 2.0 Scope This document summarizes the scale model tests performed to determine the EPU normal operation acoustic loading on the BFNI steam dryer. These tests were conducted during January and February of 2006. The following items are included in this document:

1. Description of the scale model test apparatus

2. Description of the BFNI scale model

3. Discussion of the scaling laws used to design and perform the BFNI scale model tests

4. Description of the tests performed

5. Presentation of experimental data

6. Discussion of results

7. Discussion of experimental uncertainty

8. Selection and preparation of data for input to the Load Interpolation Algorithm (LIA).

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 3.0 Description of Test Apparatus This section describes the scale test apparatus used for the BFN I scale model testing and identifies the instrumentation and data acquisition equipment used. The discussion includes both the general test facility as well as the BFNI specific scale model components.

3.1 BWR Scale Test Apparatus Figure I is a schematic of the Boiling Water Reactor (BWR) Model Acoustic Test Facility located at the General Electric (GE) Vallecitos Nuclear Center (VNC). Figure 2 is a digital image of the BWR Model Acoustic Test Facility with the BFNI plant specific main steam system scale model attached. The test apparatus consists of both the equipment and structure required for a plant specific scale model to be installed and tested and the scale model itself. The scale test apparatus designed for this test program is composed of two primary components:

1. Test fixture

2. BWR scale model The test fixture consists of the components necessary to generate and route air flow to the scale model. The plant specific scale model extends from the steam/water interface inside the Reactor Pressure Vessel (RPV) out the main steam lines to the high pressure turbine inlet and consists of the steam dryer, RPV, and main steam lines.

Ambient air is used as the test fluid. The assumptions made while designing the test facility are discussed in Reference 1, "General Electric Boiling Water Reactor Steam Dryer Scale Model Test Based Fluctuating Load Derinitioni Methodology - March 2006 Benchmark Report." Some improvements have been made to the BFNJ modeling methodology. These improvements are discussed in Sections 3.5.3.1 and 3.5.3.3. Both the test fixture and the BFNI plant specific scale model are discussed separately below.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 1: General schematic of GE BWR Model Acoustic test apparatus with the BFNI scale model attached Figure 2: Digital photograph of the GE BWR Model Acoustic test apparatus with the BFNI scale model attached Page 5 of 216

NON-PROPRIETARY VERSION G ENE-0000-0052-3661-0 1-NP 3.2 BWR Model Acousfic Test Fixture The BWR Model Acoustic Test Fixture provides the functional equipment and footprint needed to successfully attach a plant specific scale model and perform flow testing. Each of the following components can be identified in Figure 3:

1. Blowers

2. Inlet Piping

3. Flow Meter

4. Muffler The blowers provide the air flow which is routed through the inlet piping into the model.

A venturi flow meter, and muffler have been mounted between the blowers and the scale model. The venturi flow meter is used to measure the total system air flow and the muffler is used to isolate the model from the noise introduced into the system by the test fixture. This noise may consist of the blower Vane Passing Frequency (VPF), organ pipe modes associated with the inlet piping, or other white noise created by the test fixture configuration. One improvement over the earlier test fixture configuration used for the SMT Benchmark [1] is the addition of acoustically absorbent foam to the inside of the frustum that expands the diameter of the test fixture piping from the blower/muffler diameter to the RPV/dryer diameter in order to reduce any effects of acoustic modes of the frustum. It should also be noted that the angle of the inlet cone is less than 50 to prevent flow separation and the turbulent noise that would result from this.

Also shown in Figure 3 but not annotated are the two skids upon which the blowers and fnrstum are mounted. These skids are mounted on casters which allow the test facility to be moved. A plant specific BWR scale model is attached to the outlet of the frustum and to the adjacent skid. The MSL components are attached to the spine that connects the two skids. This is discussed in the following section in more detail.

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NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01-NP

/-TRI FLOW VENTURI BLOVWER -

SONIC 19150 MUFFLER-MCMASTER 2775K1 FUNNEL FLANGE ASSYW TEST RIG SUPPORT STAND-/

Figure 3: Schematic of the BWR Model Acoustic Test Fixture 3.3 Browns Ferry Nuclear Plant Unit I Plant Specific Scale Model The BFNI plant specific scale model consists of three components:

1. RPV

2. Steam Dryer

3. Main Steam Lines Each of these components can be seen in Figures I and 2. The BFNI model is built to a 1:17.3 scale. The model scale is determined by the flange diameter at the outlet of the fnrstum, the component that expands from the blower/muffler pipe diameter to the RI)V/dryer diameter. Each of the major model components introduced above are discussed below.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP The RPV is fabricated using acrylic. The main steam line nozzles and multiple microphone ports are added to the RPV cylinder by attaching acrylic blocks to the outside oftthe RPV cylinder and machining the appropriate size penetration. The MSL nozzle blend radius is added to this assembly. The top head is fabricated from stainless steel.

The radius of the top head is preserved. Figure 4 is a digital image of the BFNI RPV cylinder with the RPV top head attached.

Figure 4: Digital photograph of the BFNI RPV cylinder and top head.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP The steam dryer is fabricated from a polymer using a stereolithography (SLA) rapid prototyping process. It is then metal plated to prevent air from flowing through the model steam dryer walls. The geometry of the steam dryer is preserved. Figure 5 displays three digital photographs of the BFNI model steam dryer.

Bye r; -u , .a.

aq

[~i I

Xr-

. S F. ,He I

9' hi 9

4 t Figure 5: Digital photographs of the BFNI model steam dryer Page 9 of 216

NON-PROPRIETARY VERSION CENE-0000-0052-3661-01-NP The steam lines are fabricated from standard stainless steel piping. All Main Steam Line (MSL) valves were considered during design of the main steam line piping (Safety/Relief Valves (MSRV), Main Steam Isolation Valves (MSIV), Turbine Control Valves (TCV),

and Turbine Stop Valves (TSV)). Each valve was located at the correct location along the pipe length. The main steam lines and all branch lines greater than 2" in outer diameter at the plant scale were replicated in the scale model. The 2" diameter lower bound on the branch lines considered for this testing was selected as a lower bound diameter that could be represented in the test apparatus considering the model scale.

Figure 6 is a schematic of the BFN I model main steam lines with the significant components annotated and with the MSL designations noted. Figures 2 and 7 through 9 are digital photographs of the BFN I model main steam system.

INLET AHPCILo COW ROLVAt 3Ame MSL A L nMSL B use vMSL D Figure 6: Schematic of the BFNI model main steam system.

GOW Page 10of216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP

_ m jr- I LL \.1 Figure 7: Picture of the BFNI Scale Model Piping System AI * --

Figure 8: Picture of the BFNi Scale Model Vessel and Piping System Page 11 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 9: Picture of the BFN I Scale Model Vessel and Piping System 3.4 Model Components used for Sensitivity Testing This section describes special components designed to enable sensitivity testing of various BFNI main steam system components. These components are designed to have minimal affect on the flow distribution in the model and the acoustic characteristics of the model.

3.$.1 Standpipe Length Adjusters The standpipe length adjuster was designed to allow the length of the Blind Flange (BF) and Main Steam Relief Valve (MSRV) standpipes to be changed within the range of the uncertainty identified by TVA. This device is a piston that can be inserted into the model standpipe to a predetermined depth to set the natural frequency of the model standpipes.

The piston is sealed with an O-ring to prevent air leakage past the piston head. Figure 10 is a schematic of the standpipe length adjuster.

Page 12 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP A sensitivity study was performed on each valve and blind flange to evaluate the effect of small changes in cavity length on the fluctuating pressures measured on the dryer.

During the BFNI Baseline Tests, these length adjusters were set to the length that provided the highest amplitude response during the sensitivity testing. Section 6.2.1 details the nominal lengths and the increments used for the uncertainty testing. Figure 11 shows the standpipe length adjuster installed on MSL A and MSL B.

B r-G SOLID VIEW SECTION B-8 LB FULLY RETRACTED POSITION Figure 10: Schematic of the BF/MSRV length adjuster Page 13 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP

,-r -7 4 -

__ -,bF .'

Figure 11: Picture of the BF/MSRV length adjusters as installed 3.4.2 Main Steam Line Length Adjusters In order to evaluate the effect of the uncertainty in MSL length on the fluctuating pressures measured in the model RPV steam plenum, main steam line length adjusters were designed and installed for main steam line length sensitivity testing. These adjusters were installed in the downcomer section of the MSL between the RPV and the MSRVs. By placing the adjusters here the effect of moving all MSL sources with respect to the RPV can be evaluated. Figure 12 is a schematic of the main steam line length adjuster. For each main steam line, a length range of 2.5 inches, model scale, was covered. This range corresponds to a length uncertainty of +/- 1.8 feet at the plant scale.

The expansion and contraction angle of the MSL adjuster components is 5°. This angle is sufficiently shallow that this component is not expected to cause flow separation and introduce non-representative separation induced noise. Section 6.2.2 discusses the MSL sensitivity testing further.

Page 14 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP t-L Im M. 3 _JA Ie_7L 1 SECTION A-A Figure 12: Schematic of the MSL length adjusters 3.5 Scale Modeling Assumptions and Approximations Approximations and assumptions are usually made when designing a scale model of a system. The general modeling assumptions are discussed in Reference 1. The following sections address the model boundary conditions, the environmental conditions, the components that are approximated and the components that are omitted.

31.5.1 Boundary Conditions The following approximations have been made for the boundary conditions:

1. ((

)) This boundary is expected to maximize the reflected amplitude.

2. The upstream boundary of the model is the outlet of the steam separators. This boundary has been modeled as a ((

Page 15 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661 NP

)) Upstream of this boundary is the inlet cone (frustum) which is lined with sound absorbing foam. Beyond the frustum is the duct silencer. This configuration is an improvement over the model configuration used for the Scale Model Test (SMT) benchmark [I] because the upstream boundary now is more representative of the actual plant condition. The specific improvements are:

• The steam dryer internal resonating chamber is more accurately modeled by adding the steam separator outlet plate. This change from the SMT benchmark should improve the accuracy of the steam plenum acoustic modes inside the steam dryer.

• Acoustic absorbing foam has been added immediately upstream of the steam separator boundary condition; thereby, placing a muffler as close as possible to the upstream boundary of the scale model.

3. The turbine inlet is modeled as a drum with each main steam line attached to the drum. The relative orientation of the steam lines to each other is not controlled; however, the total steam line length is maintained at scale.

3.:5.2 Environmental Conditions The following differences exist between the environmental parameters at the test scale and the plant scale:

1. The model test fluid is air rather than saturated steam at reactor conditions.

2. The pressure ranges from 0 to 5.2 psig depending on the model system air flow rate rather than -1050 psia.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01 -NP

3. The vessel temperature ranges from 90'F to 1300 F depending on the model system air flow rate rather than -550'F. The environmental conditions during each test run are recorded and used as inputs to the pressure and frequency scaling when the SMT data are scaled to plant conditions.

3.5.3 Components Approximated This section reviews specific details of components that are approximated for the BFNI scale model test. The following components are discussed:

I. Steam Separator Outlet

2. Steam Dryer

3. Dryer Vane Banks

4. Main Steam Lines

5. Safety and Relief Valves

6. Main Steam Isolation Valves

7. Turbine Control Valves/Turbine Stop Valves 3.5.3.1 Steam Separator Outlet The steam separator outlet is approximated as a ((

)) Figure 13 is a schematic showing the separator plate installed in the steam dryer model. Addition of this component better preserves the shape of the resonating chamber inside the steam dryer between the dryer vanes and the separator outlet. This component has been added since the SMT Benchmark report [1] was prepared. Figure 14 is a digital photograph showing a bottom view of this plate as installed in the steam dryer.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP m

10 w

-4 0

Figure 13: Schematic of separator plate installed in the model steam dryer Figure 14: Picture of(( )) simulating steam separator outlet as installed in BFNI scale model Page 18 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01 -NP 3.5.3.2 Steam Dryer The outside surface of the steam dryer is a geometric replica of the plant scale dryer down to the normal water level at the outside of the dryer skirt. The inner hoods, center baffle plate, drain troughs and dryer vanes have been modeled. The dryer is fabricated with a polymer using a rapid prototyping process and is then metal plated to prevent air from flowing through the porous walls. The dryer is intended to provide an accurate representation of the acoustic volume between the outlet of the steam separators and the inside surface of the RPV and top head. No attempt has been made to ensure structural similarity of the dryer plates and supporting members; therefore, this model will not duplicate the structural response of the dryer. The dryer inner hoods are included as well as model representations of dryer vanes and perforated plate assemblies. Figure 5 contains three photographs of the BFNJ steam dryer model without the model dryer vane banks installed.

3.5.3.3 Dryer Vane Banks The steam dryer vane banks and perforated plate assemblies are approximated as 1 I]

Figures 15 and 16 show details of the vane banks installed in the scale model. Additional brackets and hardware were necessary to hold the vanes in during flow testing.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 1]

Figure 15: Picture of Perforated Plates simulating vane banks as installed in BFN1 scale model Page 20 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661 NP 1II Figure 16: Additional Detail of Perforated Plates simulating vane banks in BFNI scale model.

Page 21 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 3.5.3.4 Main Steam Line Routing, Elbows and Diameter The pipe routing of the MSLs is maintained to a location just downstream of the MSRV, HPCI, and RCIC branch lines. The local flow distribution at the mouth of a deep cavity is known to effect the flow rate at which cavity resonances are excited; therefore, the MSL routing past the MSRV must be maintained. Downstream of this location the MSL lengths between valves, D-ring, etc. are maintained. Where possible, the MSL routing is preserved.

In the scale model test rig, long radius elbows are interchanged with straight pipe sections to facilitate layout of the scale piping system. Any short radius elbows that exist at the plant are modeled in the test apparatus. Previous work has shown that long radius elbows do not change the acoustic characteristic of piping systems. Although inclusion of long radius elbows to facilitate model MASL layout is not considered to change the natural frequencies of the piping system, the elbows themselves may act as sources of turbulence induced acoustics. The MSL contains multiple ((

)) Previous work has shown that the (( )) into the model system [1]; therefore, having small differences in the number of elbows in the MSL of the model and the plant is not significant. Figure 6 displays the BFNI model MSL configuration.

The plant piping ID is reduced by the BFN I scale factor, 1: 17.3, to determine the desired model piping ID; however, the actual model piping ID is determined by the closest standard pipe size. This approximation results in a difference between desired and actual model piping ID of 0.005 inches or 0.5%.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 3.5.3.5 Safety and Relief Valves Thie MSRVs are closed during normal operation; therefore, the MSRV inlet length composed of the standpipe and valve internal cavity up to the valve seat is the only portion of the valve that is considered for the scale model. The inlet is modeled at scale as

)) of the model standpipes is consistent with the literature [Reference 2]. Furthermore, rounded edges at the entrance of a cavity have been shown to attenuate the amplitude of a cavity resonance [Reference 3]; to be conservative the GE SMT uses sharp edges.

Calculations were performed to predict the frequencies expected from the MSRVs and B'Fs. Both the MSRV and BF exhibit similar calculated frequencies to each other as shown in the table below. The frequencies were calculated using two slightly different ecuations - denoted in the table by Equation Ii and Equation lii - that account for the valve bore length and valve bore radius differently; however, both produce equivalent results.

Table 1: CIlculated Frequencics of MSRV and Blind Flange Standpipcs

((I 3.5.3.6 Main Steam Isolation Valves The MSIVs were modeled using drawing information provided by TVA. GENE designed model MSIVs that preserve the geometry of the plant MSIVs at scale. This approach will preserve the resistance coefficient of the valve body. Figure 17 is a Page 23 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP schematic of the scale MSIV, and Figure 18 is a picture of the MSIVs. The MSIV has a fixed liner and rigid guides which extend into the steam flow path.

A SECTION A-A A

A Figure 17: Schematic of the MSIV scale valve body Figure 18: Picture of the MSIV scale valve bodies as installed on the scale model test rig Page 24 of 216

NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01-NP 3.5.3.7 Turbine Control Valves/Turbine Stop Valves The TCV and TSV were modeled using two methods:

I. Simplified models using a )) of equivalent ((

))

2. Detailed geometric valve models The simplified valve models were designed consistent with the approach described in the SrMT benchmark report [1]. The TSV and the TCV are modeled by placing a ((

)) in the correct, scaled, location of the TCV along the MSL. The equalizing header that exists in the TSV body is included in the simplified valve model by placing piping tees and crosses at an equivalent location in the MSL. The ((

)) is defined such that the (( ]

is equivalent to the plant TSV/TCV assembly. The detailed valve assemblies were designed to answer the question whether the ball valve assemblies are a significant source of turbulence-induced noise in the RPV steam plenum. The detailed valve bodies were deigned by ensuring geometric similarity between the model and plant at a consistent scale, 1: 17.3. The TSV strainer has a design similar to the strainer included in the plant T'SV.

Tests were performed with both valve configurations for BFN l. These results will be discussed in the sensitivity testing section of this report.

Figure 19 is a schematic of the detailed TCV while Figure 20 is a schematic of the detailed TSV. Figure 21 is a picture of the TSV/TCV assembly, and Figure 22 is a picture of the simplified valve models.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP SECTION A-A Figure 19: Schematic of the scale Turbine Control Valve

_I SECTION AA A

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 20: Schematic of the scale Turbine Stop Valve

-i AD.----

I_ ,'._ ,

I <

Figure 21: Picture of the TCV/TSV Assembly He C__

Figure 22: Picture of the simplified TC\'/TSV Assembly Page 27 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 3.5.4 Components Omitted This section discusses which components are omitted in the scale model test. These components are listed below:

1. RPV Instrumentation Ports and Top Head Nozzles

2. Branch lines attached to MSL piping with plant scale diameters less than 2 inches 3.:5.4.1 RPV Instrnnmentation Ports and Top Head Nozzles The RPV instrumentation ports and top head nozzles are omitted. The grazing flow velocity is sufficiently low that these components are not probable sources of acoustic pressure fluctuations. The size of these components is also small enough with respect to the volume of the steam dome that exclusion of these components will not affect the acoustic characteristics of the steam dome.

3.5.4.2 Branch lines attached to MSL piping with plant scale diameters less than 2 inches These small lines in the plant scale vessel are not included in the scale model. No previous testing has shown that long branch lines contribute a significant component to the overall load experienced by the steam dryer. In addition, review of the available instrumented dryer data obtained from four BWR steam dryers does not exhibit a significant load component that appears to be contributed by a MSL branch line other than the safety and relief valves. Most branch lines attached to the MSL are very long (the safety and relief valves are the only lines that are short; they are on the order of 2 feet long). Considering the length of the long branch lines and the operational steam velocities present in the BWR MSL any cavity resonance likely to be excited in a long branch line would be a higher order organ pipe mode. Testing performed by other researchers has shown that these higher mode resonances exhibit very low amplitude resonances. Recognizing this, elimination of most branch lines could be considered; Page 28 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP however, GE has chosen to include them so that the effect they may have on the amplitude of a fluctuating pressure wave may be preserved. The 2 inch plant scale lower bound on branch lines is selected using practical considerations; at the scale chosen for the test apparatus, these small lines could not be accurately modeled.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 4.0 Scaling Factors used to convert Model data to Plant Scale Reference 1, "General Electric Boiling Water Reactor Steam Dryer Scale Model Test Based Flluctuating Load Definition Methodology- March 2006 Benchmark Report,"

Section 4.1 and Attachment A of that document, discuss the scale model relationships and scaling laws used for the BFNI SMT program. Applying these relationships to the BFNI plant operating conditions produces scale model test flow rates corresponding to BFNI power conditions such as OLTP and EPU. The scaling relationships can also be used to calculate time and pressure scaling factors necessary to convert the model data to plant conditions. For reference, the scaling relationships used to determine model flow rates as well as time and pressure scaling factors are shown below:

Model velocity corresponding to a specific power level is determined by preserving Mach number between plant and model:

(n = CPp(1 (I') )

Frequency (time) and pressure scaling factors required for converting model data to plant scale are given by:

T= 'D ., (2)

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP The scaling factors used for the Load Interpolation Algorithm (LIA) and Acoustic Circuit Model (ACM) load definitions are:

• LIA input o EPU - Time: (( )) Amplitude: (( 1]

o OLTP-Time: (( )) Amplitude: (( 1]

• ACM input o EPU - Time: (( )) Amplitude: (( ))

o OLTP-Time: (( )) Amplitude: ((

The EPU and OLTP factors for the LIA and ACM input are different because of the differences in the model static pressures and temperatures for each run. It should be noted that each model test was performed only after the system had reached a steady state temperature; however, depending on the ambient temperature of the day, the steady state fluid temperature inside the model varied for each run.

Page 31 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 5.0 Data Acquisition System and Instrumentation The following instrumentation was used to monitor the system behavior:

I. A venturi type flow meter was used to measure total system air flow

2. One Rosemont model 3051 CD2A pressure transducer was used to measure the differential pressure across the venturi flow meter. One Rosemont model 3051 CD2A pressure transducer was used to monitor the absolute static air pressure in the model.

3. Two thermocouples were used to monitor the air temperature in the system.

Measurements were taken continuously on the vessel inner surface using a plug that had been instrumented with a thermocouple. The other thermocouple was placed at the turbine outlet.

4. PCB 377A01 electret microphones with 426B03 ICP pre-amps were used to measure the unsteady pressure oscillations in the system. Most microphones were mounted such that the sensor diaphragm was flush with the outer surface of the steam dryer assembly, the inside surface of the pipe wall or the inside surface of the vessel. Exceptions to this mounting arrangement were the microphones on the dryer inner hoods and the microphones inside the dryer skirt. The dryer inner hood microphones were mounted so that the microphone axis was parallel to the panel, and the diaphragm was facing away from the flow. The microphones inside the dryer skirt were mounted with the diaphragm facing away from the flow where possible. The inner skirt microphones could not be precisely mounted in this orientation due to the separator plate. The microphones placed in the RPV and in the MSL were enclosed with a sensor mounting assembly to ensure that the microphone vent was exposed to the mean pressure inside the test fixture rather than the external ambient pressure.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661 NP The following equipment was used to record and analyze the test data:

]. The analog signal from all transducers was routed to a 108 channel LMS SCADAS Ill dynamic signal analyzer. A Dell Precision M70 laptop personal computer with 2 Gigabytes of Random Access Memory (RAM) and processor speed of 2 GigaHertz was used to control the data acquisition front end using LMS Test.Lab software. The system formed by the data acquisition front end and the computer converts the analog data to digital data, performs the signal analysis and stores the throughput data in digital format. Two runs were made for each test condition - one run that contained eight MSL microphones and another run that moved these microphones to the vessel. All of the dryer channels were kept during each run as well as some vessel channels.

Figure 22 is a layout of the data acquisition system. The TS&P contains the test data sheets, instrument log, tape log, and calibration information for all equipment used for these tests.

o-1,.

Figure 23: Block Diagram of Data Acquisition and Blower Control System Page 33 of216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 5.1 Sensor Locations Microphones were placed on the following components:

Steam Dryer

.RPV

. MSL Figures 24 through 28 are schematics and pictures of the dryer with the microphone locations identified. For each dryer face, both a schematic and a digital image showing the chosen sensor locations is provided. There is an interior microphone in addition to the exterior microphone where there are two numbers marked on the dryer outer surface.

Eighteen microphone locations were selected on the BFNI model dryer. These locations were chosen to obtain data at locations previously instrumented during plant or model test programs and to obtain data that could be used to assess the accuracy of the LIA.

The dryer microphone locations are distributed as follows:

• 10 microphones on the outside surface of the steam dryer,

• 2 microphones on the inner hoods,

• 6 microphones on the inside of the steam dryer o 4 in the skirt region and o 2 near the lower part of the outer hood.

Fifty-three microphones were either divided among the vessel locations and the 8 MSL locations or located solely on the vessel. Figure 29 depicts the microphone locations on the vessel in a schematic. This schematic contains a nomenclature used to identify the location a microphone was placed on the RPV. Microphone locations were selected such that microphone locations were distributed around the circumference of the RPV. Figure 30 is a schematic identifying the MSL microphone locations on each of the four MSL.

Also included on this drawing are the MSL centerline distances between the OD of the RPV and the location of the microphone. Figure 31 is a picture that showvs the vessel microphone locations on the MSL CID side of the vessel.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP The MSL microphone locations were chosen to correspond to the location of the MSL fluctuating pressure instrumentation to be placed on BFNI during power ascension testing. Figures 31 and 32 are pictures that show some of the microphone locations on the main steam lines.

Tables 2 and 3 list the sensor locations and identify the test group specified for each sensor. Included as a note to these tables are the steam dryer microphones placed on the inside of the dryer.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP

© DENOTES MICROPHONE PLACED ON INSIDE & OUTSIDE SURFACE OF STEAM DRYER.

0 DENOTES MICROPHONE PLACED FLUSH AITH OJTSIDE SURFACE OF DRYER.

rwtu muu Figure 24: Picture of the 0° Side with Sensor Locations Page 36 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP

© DENOTES MiCROPHONE PLACED ON INSIDE & OUTSIDE SURFACE OF STEAM DRYER.

0 DENOTES MICROPHONE PLACED FLUSH V11THOUTSIDE SURFACE OF DRYER.

-dd-WI Figure 25: Picture of the 900 Side with Sensor Locations Page 37 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP

© DENOTES MICROPHONE PLACED ON INS:DE & OUTSIDE SURFACE OF STEAM DRYER.

0 DENOTES MDCROr4IONE PLACED FLUSH WITH OUTSIDE SURFACE OF DRYER.

Figure 26: Picture of the 1800 Side wvith Sensor Locations Page 38 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661 NP 7 1 I 1 I1 F I AMI

© DENOTES MICROPHONE PLACED ON INSIDE & OUTSIDE SURFACE OF STEAM DRYER.

0 DENOTES M/ICROPHONE PLACED FLUSH WATHOUTSIDE SURFACE OF DRYER.

Figure 27: Picture of the 270° Side with Sensor Locations Page 39 of 216

NON-PROPRIETARY VERSION G ENE-0000-0052-3661 NP i 001 I I I 0 I

I I I ,

© DENOTES MICROPHONE PLACED ON INSIDE & OUTSIDE SURFACE OF STEAM DRYER.

Q DENOTES IICROPHOtE PLACED FLUSH WTH OUTSIDE SURFACE Of DRYER Microphone Locatio Indicated by Circles

/

Figure 28: Picture of the Dryer Top wmith Sensor Locations

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01 -NP

__4D NO. ARE FOR R WILL NOT APPEAF Figure 29: Schematic of the Vessel with Sensor Locations Page 41 of 216

NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01-NP BYRO ttCUNTlL¢ERtE LUXTHz 0 TOE Is LLTRANGIE-Is 0

0A eFCR 5ROX 5 ALL4 LErSS1 I STIO CErr GA lt/ SRA-A M SRANf§T 0 Tf~j 2wv S7RAIN CAC.F

/./ \S '

' - A 1'Ar, O SECTION A-A Figure 30: Schematic of the MSL Sensor Locations (microphones in scale model, strain gages at plant)

Page 42 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 31: Picture of the MSL C/D side of Vessel with Sensor Locations and with MSL C and D Sensor Locations Figure 32: Picture of the MSL C/D side with MSL C and D Sensor Locations Highlighted in Yellow Page 43 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Tablc 2a: Clhanncl List for Initial Run withl Vcsscl Mics onl%' - uscd for LIA Input

_ _ VesselMicsOnlyGroupl SCADAS Sensor SCADAS Sensor Chnnel Number/ Channel Number/

Nunber Identification Description/Location Nurrber Identification Description/Location

_ M:1 Microphone/Dryer 29 V:26 MicrophoneNessel 2 M:2 Microphone/Dryer 30 V:27 MicrophoneNessel 3 M:3 Microphone/Dryer 31 V:28 MicrophoneNessel 4 M:4 Microphone/Dryer 32 V:32 MicrophoneNessel 5 M:5 Microphone/Dryer 33 V:33 MicrophoneNessel 6 M:6 Microphone/Dryer 34 V:34 MicrophoneNessel 7 M:7 Microphone/Dryer 35 V:29 MicrophoneNessel 8 M:8 Microphone/Dryer 36 V:17 MicrophoneNessel 9 M:9 Microphone/Dryer 37 V:30 MicrophoneNessel 10 M:10 Microphone/Dryer 38 V:82 MicrophoneNessel 11 M:11 Microphone/Dryer 39 V:81 MicrophoneNessel 12 M:12 Microphone/Dryer 41 V:79 MicrophoneNessel 13 M:13 Microphone/Dryer 42 V:78 MicrophoneNessel 14 M:14 Microphone/Dryer 43 V:65 MicrophoneNessel 15 M:15 Microphone/Dryer 44 V:74 MicrophoneNessel 16 M:16 Microphone/Dryer 45 V:73 MicrophoneNessel 17 M:17 Microphone/Dryer 46 V:72 MicrophoneNessel 18 M:18 Microphone/Dryer 47 V:71 MicrophoneNessel 19 V:48 MicrophoneNessel 48 V:70 MicrophoneNessel 20 V:89 MicrophoneNessel 49 V:75 MicrophoneNessel 21 V:55 MicrophoneNessel 50 V:61 MicrophoneNessel 22 V:86 MicrophoneNessel 51 V:60 MicrophoneNessel 23 V:38 MicrophoneNessel 52 V:59 MicrophoneNessel 24 V:45 MicrophoneNessel 53 V:58 MicrophoneNessel 25 VA MicrophoneNessel 54 V:57 MicrophoneNessel 26 V:92 MicrophoneNessel 55 V:63 MicrophoneNessel 27 V:35 MicrophoneNessel 56 V:62 MicrophoneNessel 28 V:7 MicrophoneNessel 57 V:69 MicrophonelVessel Nctc: The following microphonc locations are in tlic intcrior surfacc of the BFN I niodel diycr:

M:l M:5 M:8 M:I]

M:13 M: 16 Page 44 of 216

NON-PROPRIETARY VERSION G ENE-0000-0052-366 1-01-NP Tablc 2b: Rciniinder of Clhanncl List for Initial Run -itli Vcsscl Mics onl - uscd for LIA Input

-Y VesselMics~nlvGrou[)1 SCADAS Channel Sensor Number/

Number Identification Description/Location 58 V:68 MicrophoneNessel 59 V:67 MicrophoneNessel 60 V:66 MicrophoneNessel 61 V:11 MicrophoneNessel 62 V:12 MicrophoneNessel 63 V:13 MicrophoneNessel 64 V:14 MicrophoneNessel 65 V:15 MicrophoneNessel 66 V:16 MicrophoneNessel 67 V:19 MicrophoneNessel 68 V:20 MicrophoneNessel 69 V:21 MicrophoneNessel 70 V:22 MicrophoneNessel 71 V:23 MicrophoneNessel 72 V:24 MicrophoneNessel 73 V:25 MicrophoneNessel 74 V:80 MicrophoneNessel 81 Flow Voltage/Flow 82 StaticPressure Voltage/Static Pressure 83 VsslTemp VoltageNessel Temperature Voltage/Turbine Outlet 84 TurbTemp Temperature Page 45 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Tablc 3a: Clianncl List for Initial Run with MSL jnicroplioncs - uscd for ACM Input

___ _ WithMSLMics _

3A*ADAs Sensor SCADAS Sensor Channel Number/ Channel Number/

Number Identification Description/Location Number Identification Description/Location 1 M:1 Microphone/Dryer 29 V:26 MicrophoneNessel 2 M:2 Microphone/Dryer 30 V:27 MicrophoneNessel 3 M:3 Microphone/Dryer 31 V:28 MicrophoneNessel 4 M:4 Microphone/Dryer 32 V:32 MicrophoneNessel 5 M:5 Microphone/Dryer 33 V:33 MicrophoneNessel 6 M:6 Microphone/Dryer 34 V:34 MicrophoneNessel 7 M:7 Microphone/Dryer 35 V:29 MicrophoneNessel 8 M:8 Microphone/Dryer 36 V:17 MicrophoneNessel 9 M:9 Microphone/Dryer 37 V:30 MicrophoneNessel 10 M:10 Microphone/Dryer 38 V:82 MicrophoneNessel 11 M:11 Microphone/Dryer 39 V:81 MicrophoneNessel 12 M:12 Microphone/Dryer 41 V:79 MicrophoneNessel 13 M:13 Microphone/Dryer 42 V:78 MicrophoneNessel 14 M:14 Microphone/Dryer 43 V:65 MicrophoneNessel 15 M:15 Microphone/Dryer 44 V:74 MicrophoneNessel 16 M:16 Microphone/Dryer 45 V:73 MicrophoneNessel 17 M:17 Microphone/Dryer 46 V:72 MicrophoneNessel 18 M:18 Microphone/Dryer 47 V:71 MicrophoneNessel 19 P:1001 Microphone/After Muffler 48 V:70 MicrophoneNessel 20 P:999 Microphone/Before Muffler 49 V:75 Microphone/essel Microphone/MSLA along MSL CL from outside 21 MSLA:1 of vessel wall 50 V:61 MicrophoneNessel Microphone/MSL A 22.4 in_

along MSL CL from outside 22 MSL A:2 of vessel wall 51 V:60 MicrophoneNessel Microphone/MSL B 8.8 in.

along MSL CL from outside 23 MSL B:1 of vessel wall 52 V:59 MicrophoneNessel Microphone/MSL B 22.0 in.

along MSL CL from outside 24 MSL B:2 of vessel wall 53 V:58 MicrophoneNessel Microphone/MSL C 8.8 in.

along MSL CL from outside 25 MSL C:1 of vessel wall 54 V:57 MicrophoneNessel Microphone/MSL C 22.0 In.

along MSL CL from outside 26 MSL C:2 of vessel wall 55 V:63 MicrophoneNessel Microphone/MSL D 8.8 In.

along MSL CL from outside 27 MSL D:1 of vessel wall 56 V:62 MicrophoneNessel

_MicrophonelMSL D 22.4 in.

along MSL CL from outside 28 MSL D:2 of vessel wall 57 V:69 MicrophoneNessel Page 46 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661 NP Tabic 3b: Rcniaindcr of Channcl List for Initial Run wvith MSL microplhoncs - uscd for ACM Input WithMSLMics SCADAS Sensor Channel Number/

Number Identification Description/Location 58 V:68 MicrophoneNessel 59 V:67 MicrophoneNessel 60 V:66 MicrophoneNessel 61 V:11 MicrophoneNessel 62 V:12 MicrophoneNessel 63 V:13 MicrophoneNessel 64 V:14 MicrophoneNessel 65 V:15 MicrophoneNessel 66 V:16 MicrophoneNessel 67 V:19 MicrophoneNessel 68 V:20 MicrophoneNessel 69 V:21 MicrophoneNessel 70 V:22 MicrophoneNessel 71 V:23 MicrophoneNessel 72 V:24 MicrophoneNessel 73 V:25 MicrophoneNessel 74 V:80 MicrophoneNessel 81 Flow Voltage/Flow 82 otaticPressurE Voltage/Static Pressure 83 VsslTemp VoltageNessel Temperature Voltage/Turbine Outlet 84 TurbTemp Temperature Page 47 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 6.0 Test Matrix Three types of tests were conducted with the BFN I scale model:

1. Characterization Testing

2. Sensitivity Testing

3. Baseline Testing The following sections provide further description of each type of test.

6.1 Characterization Testing Characterization testing was performed to acquire data that could be used to correlate the acoustic Finite Element Model (FEM) of the physical model. The acoustic FEM was used to predict the normal modes of the steam system. These modes were used to help interpret the frequency content and spatial pressure distribution of the data acquired in the steam plenum and as input to the LIA. The acoustic FEM is discussed in more detail in a separate document for BFN l.

The characterization testing was performed by injecting a known noise source at various locations in the physical model and measuring the response at other locations. The noise source was a Mid-Frequency Volume Velocity Source (MFVVS), a device that provides a calibrated and controllable acoustic source and measures the volume acceleration that it imparts at its acoustic center or focal point. Volume acceleration is independent of boundary conditions so it is a consistent indicator of source strength. The volume velocity source is used as the reference, or input, and the microphones on the dryer and in the main steam lines are used as responses, or outputs, to calculate Frequency Response Functions (FRF). Several different types of input were evaluated:

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1. Periodic Chirp - a sine signal that, during the data acquisition period, is swept rapidly through the frequency range of interest. In this set of tests, it lasted for 70% of the acquisition time.

2. Burst Random - a pure random signal in the frequency range of interest that is generated for only a portion of the time that is required to acquire a block of data and then drops to zero level for the remainder of the acquisition time. In this testing, it lasted for 70% of the acquisition time with a very brief ramp at the beginning of the acquisition.

3. Random - a pure random signal that is continuous for the data acquisition period.

The different source types provided consistent results; however, in the frequency range of interest, the periodic chirp source generally provided the highest coherence value. The periodic chirp results were used primarily for the analysis and comparisons with the acoustic FEM results.

The testing consisted of inserting the source at a known location and operating the source with the data acquisition system to obtain spectral results - FRFs, input autopower and response autopowers - that are the average of 100 individual measurements.

Measurements were performed with the source located in one of the RPV MSL nozzles and plugs inserted into the remaining three MSL nozzles and with a rigid boundary at the steam-water interface inside the steam dryer at the outlet flange of the cone. Figure 33 illustrates this configuration. These tests were performed without flow in the system.

There was also some testing done with flow, with the plugs replaced by the first elbows out of the RPV, in order to determine the effects of flow on the system.

The FRFs calculated from the test data were compared against FRFs calculated from the acoustic FEM to identify deficiencies in the acoustic FEM. The FRFs were also curve fit in an experimental acoustic modal analysis to obtain mode shapes of the acoustic space with associated frequency and damping values. The acoustic FEM was then modified, Page 49 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP where appropriate, to improve the correlation - both to more closely match the frequencies of corresponding mode shapes from experiment to acoustic FEM and to increase the similarity between experimental and acoustic FRFs. This process is an acoustic analogy to a structural experimental modal analysis being performed to update a structural FEM. The volume velocity source is analogous to a shaker that provides an input force, and the microphones are analogous to accelerometers that provide an output acceleration. In the structural case, acceleration per force FRFs are obtained. In the acoustic case, pressure per volume acceleration FRFs are obtained. This process is described in more detail in the Acoustic Finite Element Modeling Report for BFN 1.

1-! 4UvAiSnoeurcen AL SECTION AV S Rigid boundary Figure 33: Model configuration for characterization testing.

6.2 Sensitivity Testing Sensitivity testing refers to tests performed to determine the effect on the steam dryer fluctuating loads caused by:

• Changes to model parameters within their expected range of geometric uncertainty

• Modeling assumptions.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP The specific parameters studied during this testing were:

• Blind Flange/ MSRV length

• MSL length

• TSV/TCV configuration 6.2.1 Blind Flange/ Main Steam Relief Valve Sensitivity Tests Table 4 lists the specific BF and MSRV settings used during the sensitivity testing. The standpipe lengths were adjusted using the standpipe length adjusters described in Section

3. .1. With all other valves at their nominal positions, each valve individually wvas varied, and the effect on the fluctuating pressures measured by the dryer microphones was observed. These observations were recorded in a test log to be used durin, the baseline testing.

Table 4: Standpipe Lengths Scale Model Scale Model Plant Nominal Nominal Length Sensitivity lain Steam Standpipe Length from from MSL CL Adjustment Line Identification Type MSL CL [inches) [inches) [inches]

A Valve I SRV 50.6 2.924 +/- 0.060 A Valve 2 BF 31.4 1.817 +/- 0.030 A Valve 3 BF 31.4 1.817 +/- 0.030 A Valve 4 SRV 50.6 2.924 +/- 0.060 A Valve 5 BF 31.4 1.817 +/- 0.030 A Valve 6 BF 31.4 1.817 +/- 0.030 A Valve 7 SRV 50.6 2.924 +/- 0.060 B Valve 1 BF 31.4 1.817 +/- 0.030 B Valve 2 BF 31.4 1.817 +/- 0.030 B Valve 3 SRV 50.6 2.924 +/- 0.060 B Valve 4 SRV 50.6 2.924 +/- 0.060 B Valve 5 SRV 50.6 2.924 +/- 0.060 B Valve 6 SRV 50.6 2.924 +/- 0.060 C Valve 1 BF 31.4 1.817 +/- 0.030 o Valve 2 BF 31.4 1.817 +/- 0.030 C Valve 3 SRV 50.6 2.924 +/- 0.060 C Valve 4 SRV 50.6 2.924 +/- 0.060 C Valve 5 SRV 50.6 2.924 +/- 0.060 o Valve 1 SRV 50.6 2.924 +/- 0.060 D Valve 2 BF 31.4 1.817 +/- 0.030 D Valve 3 BF 31.4 1.817 +/- 0.030 D Valve 4 SRV 50.6 2.924 +/- 0.060 D Valve 5 BF 31.4 1.817 +/- 0.030 o Valve 6 BF 31.4 1.817 +/- 0.030 D Valve 7 SRV 50.6 2.924 +/- 0.060 Page 51 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661 NP 6.2.2 Main Steam Line Length Sensitivity Tests The MSL length sensitivity was studied by installing the MSL length adjusters discussed in Section 3.4.2. With these adjusters installed, the D-ring and TCV/TSV assemblies were removed so that the length of each line could vary individually. This configuration is shown in Figure 34. A baseline or nominal measurement was recorded, then the MSL length adjuster was adjusted through a range of lengths. This range included the nominal length as its center position and 0.25 inch increments up to +/-1.25 inches. These increments are listed below:

. Nominal

• Nominal +/-0.25 inches

• Nominal +/-0.50 inches

• Nominal +/-0.75 inches

• Nominal +/-1.00 inches

• Nominal +/-1.25 inches The measurements were performed, and (Root-Mean-Square) RMS levels and peak amplitudes were observed. These results are discussed in Section 8.1.2.

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w E.

Figure 34: Schematic of model configuration used for MSL length sensitivity tests.

6.2.3 Turbine Control and Turbine Stop Valve Sensitivity Tests Tests were performed with both the simplified and detailed TSV/TCV assemblies installed in the scale model. These tests were performed to assess whether the TSV/TCV valve geometries were a significant source of turbulence-induced noise in the RPV steam plenum. The results of these tests are discussed in Section 8.1.3.

6.3 Baseline Testing These tests were performed to acquire data throughout the range of expected plant operating conditions from which:

A general understanding of the BFNI steam system behavior could be obtained,

• Data could be acquired to develop load predictions at OLTP and EPU conditions.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Based on the results of the MSRV sensitivity testing, the MSRVs were adjusted to provide the maximum response at the dryer within the range of MSRV cavity length uncertainty. The specific settings are that all valves are at nominal as described in Table 3 except the following:

1. ((

2.

3. ))

Sweep and dwell tests were performed. The model flow rates calculated for OLTP and EIPU power conditions at the plant were determined using the scaling laws presented in Section 4. The sweep test ranged from 140 CFM to 350 CFM at a rate of 20 CIFM/minute. The actual OLTP and EPU flow rates for the dwell tests are determined during each run using the steady state model temperature; however, the approximate flow rates used to define the sweep test range were determined, assuming a vessel temperature of 120 'F, to be 241 ft3 /min (CFM) for OLTP and 296.4 CFM for EPU. After the sweep test results were reviewed, an additional dwell test was performed between OLTP and EP'U at -285 CFM. The tests were performed both with eight microphones on the MSLs, and with all possible microphones on the vessel. The set with eight microphones on the MSL is to be used for load prediction using the Acoustic Circuit Model (ACM), and the set with all possible microphones on the vessel is to be used for load prediction using the Load Interpolation Algorithm (LIA).

The test fluid static pressure and temperature remained within the following range for all tests:

Static Pressure: 14.7 < p < 19 psia Mean Vessel Temperature: 60 'F < T < 140 'F Page 54 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Because the system temperature and pressure increase as the blower output increases, the actual model flow rates which correspond to specific plant power levels (OLTP, EPU) are calculated during each test using the measured temperature to calculate the model sound speed.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 7.0 Data Analysis Methods This section provides a description of the data acquisition, reduction and analysis performed for the BFNI SMT.

7.1.1 Data Acquisition Tables 2 and 3 in Section 5.1 list the sensor locations used for the BFNI tests. Section 5.0 provides details of the equipment used and the initial conditioning of the transducer signals. The 108-clhannel (twenty-seven 4-channel PQFA modules) system of two LMS SCADAS III Model 316 data acquisition front ends in a master-slave configuration controlled by a personal computer (PC) equipped with LMS Test.Lab software, revision 6A SLI, received these transducer signals as analog voltages. The specific software module used during data acquisition was Signature Testing with the Time Recording During Signature Acquisition add-in. The front end performs an analog to digital conversion on the signal and transfers the signal to the PC where all of the signals from one run are stored in a throughput file, an LMS format of amplitude versus time. The initial digitization was performed with the following parameters:

• 16384 Hz sampling rate for pressure transducer signals

• 256 Hz for venturi pressure transducer signal and vessel pressure transducer signal and for thermocouple signals

• AC coupling on dryer, vessel and MSL microphone signals

• DC coupling on venturi pressure transducer signal and vessel pressure transducer signal and for thermocouple signals

• 30 seconds of raw time data (throughput) recorded for dwells

• 680 to 740 seconds of raw time data (throughput) recorded for the 140 CFM to 350 CFM sweep Page 56 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP While the raw time data was being recorded, autopower spectra were simultaneously being acquired as well. The description of that processing is included below.

7.1.2 Data Processing The data processing involved the conversion of the raw time data for the dryer, RPV, and MSL microphones in the throughput files (or original raw time domain data files) to the following output formats:

• Peak Hold Autopower Spectra

• Peak Iold Autopower Spectra with amplitude and frequency scaled from model scale to plant scale

• Linear average Autopower Spectra

• Linear average Autopower Spectra with amplitude and frequency scaled from model scale to plant scale

• Linear average Crosspower Spectra/Operating Deflection Shape

• RMS Level of Frequency Band versus time and flow TIde software module used for processing was Throughput Validation and Processing Host with the following add-ins:

• Signature Throughput Processing

• Time Signal Calculator

• Geometry

• Operating Deflection Shape

• Signature Post-Processing

• Batch Reporting Page 57 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 7.1.2.1 Peak Hold Autopower Spectra The peak hold autopower spectra were processed from the throughput files with the following parameters:

• 0 Hz to 6400 Hz frequency range

• 1 Hz frequency resolution (2 Hz for online processed results)

• Hanning Window

• 0 to peak amplitude

• linear (square root of autopower) units

• linear or no weighting

• peak hold averaging

• 2 averages per second

• For the sweep, these spectra were calculated for the flow range of 140 to 350 CFM 7.1.2.2 Peak Hold Autopower Spectra Scaled to Plant Scale To scale the data to plant scale, the original throughput files were converted to a format compatible with LMS Cada-X software and imported into Time Data Processing Monitor. In this software module, the data was multiplied by a scalar representing the amplitude scaling factor, then the time axis was edited based on the time/frequency scaling factor. The scaling factors are discussed in Section 4.0. The scaled throughput fil es were processed using Test.Lab software with the following parameters:

• 0 Hz to 400 Hz frequency range

• 0.25 Hz frequency resolution

• Hanning Window

• 0 to peak amplitude

• linear (square root of autopower) units Page 58 of 216

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• linear or no weighting

• peak hold averaging

• 1 average per second for the dwell condition

• For the sweep, these spectra were calculated for the flow range of 140 to 350 CFM 7.1.2.3 Linear Average Autopower Spectra Linear average autopower spectra were processed from the dwell throughput files using the following parameters:

• 0 Hz to 6400 Hz frequency range

• 1 Hz frequency resolution (2 Hz for online processed results)

• Hanning Window

• 0 to peak amplitude

• linear (square root of autopower) units

• linear or no weighting

• linear averaging

• 2 averages per second for the dwell condition

• 1 measurement of I average every 10 seconds for the flow sweep 7.1.2.4 Linear Average A utopower Spectra Scaled to Plant Scale The process used to scale the time records is discussed in Section 7.1.2.2. Linear average autopower spectra were processed from the dwell throughput files using the following parameters:

• 0 Hz to 400 Hz frequency range

• 0.25 Hz frequency resolution

• Hanning Window Page 59 of 216

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• 0 to peak amplitude

• linear (square root of autopower) units

• linear or no weighting

• linear averaging lI average per second for the dwell condition

• 1 measurement of I average every 60 seconds for the flow sweep 7.1.2.5 Linear Average Crosspower Spectra Linear average crosspower spectra were processed from the dwell throughput files using the following parameters:

• 0 Hz to 6400 Hz frequency range 1 Hz frequency resolution

• Hanning Window

• 0 to peak amplitude

• power units

• linear or no weighting

• linear averaging

• 2 averages per second

Reference:

M:2 (dryer outer hood location) fluctuating pressure The linear average crosspower spectra were used to produce operating pressure shapes from the dwell conditions. The measurement locations from two sets of data were used.

The additional locations from the second set were merged into the first set.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 7.1.2.6 RMS Level of Frequency Band versus time and flow Frequency bands were selected from the sweep data based on the following input:

Frequency bands, as discussed in the SMT Benchmark Report [1], that have a common source or group of sources for the whole frequency band Visually reviewing the waterfall or color map plots and using cursors to select borders of frequency bands that appeared significant.

The rms levels of these bands were calculated. The venturi pressure signal, static pressure signal and vessel temperature were processed to reflect volumetric flow rate.

The volumetric flow rate was normalized to estimated 100% power flow velocity. The mis level of the frequency bands was then plotted against the normalized flow rate it corresponded to.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 8.0 Presentation of Results This section presents the results of the sensitivity testing and the baseline testing.

Acoustic modal results will be presented in a separate document that covers the building, correlation and updating of the acoustic finite element model.

8.1 Sensitivity Testing The goals of the sensitivity testing were to:

1. Determine what valve settings, within the'valve standpipe range of uncertainty, produced the highest amplitude response at the dryer,

2. Determine the effect of MSL length variation, within the range of uncertainty, on the steam plenum acoustic loads,

3. Determine the effect of the geometrically detailed TSVTCV assembly.

This section presents the results of those sensitivity tests.

8.1.1 Blind Flange and Main Steam Relief Valve Sensitivity Tests During the BF and MSRV sensitivity tests, the length of the BF and MSRV standpipes were adjusted throughout their range of inlet length uncertainty. The length uncertainty was defined by the utility customer. Measurements were performed, and valve positions producing increased response were noted. After the effect of each valve was observed by changing one valve length at a time, the BFNI model was configured to replicate the condition that produced the maximum response for each individual valve. ((

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2.

3. ))

With these adjusted settings, the dryer outer hood sensors consistently show ((

)) The adjusted settings were used for the baseline test runs.

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((

II Figure 35: Comparison of Response at Dryer Location M:2 with Nomilnal Valve Settings (Green) and Adjusted Valvc Settings (Red) at EPU.

1]

Figure 36: Comparison of Response at Dryer Location M:3 with Nomini:al V'alve Settings (Green) and Adjusted Valve Settings (Red) at EPU.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 37: Comparison of Response at Dryer Location M:9 with Nominial Valve Settings (Green) and Adjusted Valve Settings (Red) at EPU.

Figure 38: Comparison of Response at Dryer Location M: 10with Nominal Valve Settings (Green) and Adjusted Valve Settings (Red) at EPU.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 8.1.2 Main Stearn Line Length Sensitivity Tests The MSL length sensitivity testing was performed by varying the MSL lengths between the RPV and the MSRVs through their length uncertainty. While this testing was performed, the D-ring and the TSV/TCV assembly were disconnected so that the length of one MSL could vary with respect to the others. This configuration is shown in Figure 341, and Figure 39 and 40 compare the results with and without the D-ring at two of the outer hood locations. For the MSL length sensitivity study, a measurement at nominal length was performed, then the MSL length was increased in 0.25 inch increments to 1.25 inches. Another measurement at nominal length was performed, and then the MSL length was decreased in 0.25 inch increments to -1.25 inches. ((

)) Figure 41 is an autopower comparison as the length of the MSLs were adjusted as described above. ((

)) Its amplitude was tracked during the measurements. Figures 42 through 45 contain rms levels of a frequency band approximately 100 Hz to 120 Hz wide around this peak and peak amplitudes for the peak for the different length settings. The width of the band stayed consistent within the length study of each MSL but varied from MSL to MSL to best capture the peak. Both nominal measurements are shown to provide some indication of repeatability. ((

)) Tables 5a through 5d follow the figures, and show the change in rms level of the frequency bands of interest at the outer hood microphone locations as the MSL length is varied for MSL A through D, respectively:

• [

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((

1]

Figure 39: Comparison of Response at Dryer Location M:2 with Nominal Valve Settings (Green) and No D-Ring (Red) at EPU.

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((

~1]

Figure 40: Comparison of Response at Dryer Location M:10 with Nominal Valve Settings (Green) and No D-Ring (Red) at EPU.

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Figure 41: Autopowers Acquired During MSL A Length Sensitivity Study at EPU.

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))

Figure 42: RMS Level and Peak Amplitude for (( )) Hz Peak During MSL A Length Sensitivity Study at EPU.

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((

1]

Figure 43: RMS Level and Peak Amplitude for (( )) Hz Peak During MSL B Length Sensitivity Study at EPU.

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((

Figure 44: RMS Level and Peak Amplitude for (( )) Hz Peak During MSL C Length Sensitivity Study at EPU.

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))

Figure 45: RMS Level and Peak Amplitude for (( )) Hz Peak During MSL D Lengyth Sensitivity Study at EPU.

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NON-PROPRIETARY VERSION NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Tablc 5a: RMS Lcvel Rcsulls from Frequency Bands for MSL A Length Scnsitivity

))

Tablc 5b: RMS Lc%cl Rcsuils from Frequency Bands for MSL B Lcngtlh Scnsitivitv 1]

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NON-PROPRIETARY VERSION NON-PROPRIETARY VERSION GENE-0000-0052-3661 NP Table 5c: RMS Lcvel Rcsults from Frcqticncy Bands for MSL C Lcngth Sensitivity 1]

Table 5d: RMS Levcl Rcsults from Frtqucncy Bands for MSL D Lengil Scnsitivily

((

1]

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NON-PROPRIETARY VERSION GENE-0000-0052-3661 NP 8.1.3 Effect of Geometrically Detailed Turbine Stop Valvesr/urbine Control Valves The purpose of this test was to assess whether the TSV/TCV was a significant source of noise in the RPV steam plenum. One of the simplifying assumptions made during the QC SMT [1] was ff

)) The opportunity existed in the BFNI SMT to test this assumption; therefore, both a simplified TSV/TCV and a detailed TSV/TCV assembly was designed. The BFNI scale model was tested with both. The geometrically detailed TSV/TCVs ((

)). Table 6 contains rms levels for the frequency band of interest, (( )] at the model scale, for several dryer exterior locations. Figures 46 through 49 are plots of responses on the dryer showing the comparison between operation with simple TSV/TCVs and with geometrically detailed TSV/TCVs. The geometrically detailed TSV/TCVs produce

))

Table 6: RMS Level for [f 11 Band (Model Scale) ror Simple TSVITCV and Gcornctrically Detailcd TSV/TCV Page 77 of 216

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))

Figure 46: Comparison of Response at Dryer Location M:2 with Geometrically Detailed TSV/TCVs (Green) and Simple TSV/TCVs (Red) at EPU.

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NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01-NP Figure 47: Comparison of Response at Dryer Location M:4 with Geometrically Detailed TSV/TCVs (Green) and Simple TSV/TCVs (Red) at EPU.

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I]

Figure 48: Comparison of Response at Dryer Location M:10 witl Geonictrienlly Detailed TSV/TCVs (Green) and Simple TSV/TCVs (Red) at EPU.

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Figure 49: Comparison of Response at Dryer Location M:15 with Geometrically Detailed TSV/TCVs (Green) and Simple TSV/TCVs (Red) at EPU.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 8.2 Baseline Testing The primary goals of the baseline testing were to:

1. Obtain information predicting the system response from power levels up to and beyond EPU operation

2. Obtain data for input to the structural load generation processes.

TVIA requested that GE provide a SMT load prediction and requested that GE provide SMT data to CDI for a secondary load definition based on the GE SMT data.Section II discusses the input to the LIA and ACM. This section presents some of the baseline testing results. The appendices contain a complete set of results for the baseline testing but without discussion. Appendices A and B contain peak hold and linear average autopower results from dryer microphones for the whole time records representing EPU, from which segments were chosen as input to the LIA and ACM respectively.

Appendices C and D are similar results for OLTP. Appendix E contains spectrograms of the dryer microphone data obtained from the sweep test. The following sections discuss specific aspects of the baseline testing.

8.2.1 Steady State Results In general, EPU signals are higher than OLTP. . Figures 50 through 55 show some comparisons between the two conditions. Because the loads are primarily acoustic, the frequency content is controlled by the system geometry rather than the flow velocity.

This characteristic is shown by observing the same frequency content present at both power levels displayed in Figures 50 through 55. Although the frequency content is controlled by geometry, the amplitude is controlled by flow; therefore, the amplitude at EF'U is generally higher than at OLTP.

Figcures 56 through 58 compare interior and exterior sensors at common points on the dryer. ((

)) This behavior is consistent with the Page 82 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP plant data described in Reference 1. The data shown in Figures 56 through 58 are displayed in model scale; whereas, the data shown in Figures 50 through 55 are displayed at the plant scale.

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((

11 Figure 50: EPU (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor M:2, 2700 Outer Hood Lower Corner Page 84 of 216

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((

1]

Figure 51: EIPIJ (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor M:9, 2700 Outer Hood Upper Corner Page 85 of 216

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((

1]

Figure 52: EPU (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor M: 17, 2700 Inner Hood Page 86 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 1I' Figure 53: EPIJ (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor M:7, 1800 Skirt Page 87 of 216

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[1 1]

Figure 54: EPUJ (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor M:4, 2708 Skirt Page 88 of 216

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((

Figure 55: EPU (Green) and OLTP (Red) Autopowers from whole time record of ACM input dataset for Sensor MSL C: 1, Main Steam Line C Page 89 of 216

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Figure 56: Comparison of Dryer Interior and Dryer Exterior Response at Lower Corner of Outer Hood, 2700 Face, Dryer Locations M:2, Exterior (Green) and M: 1, Interior (Red) at EPU.

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Figure 57: Comparison of Dryer Interior and Dryer Exterior Response at Skirt, 2700 Face, Dryer Locations M1:4, Exterior (Green) and M:5, Interior (Red) at EPU.

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))

Figure 58: Comparison of Dryer Interior and Dryer Exterior Response at Skirt, 180° Face, Dryer Locations M:7, Exterior (Green) and M:8, Interior (Red) at EPU.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 59 compares the three of the four main transducer locations: MSL, dryer outer hood, and dryer interior at outer hood while Figure 60 includes the inner hood in this cc mparison. ((

)) The trends among the different locations are similar to those noted in Reference 1, Sections 3 and 6 as well.

))

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((

Figure 59: Comparison of MSL, Dryer Outer Hood, and Interior of Dryer Outer Hood Responses 2700 Face: MSL C:I, MSL (Red), M:2, Outer Hood (Green), and M:I, Interior of Outer Hood (Blue) at EPU (converted to plant scale)

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))

Figure 60: Comparison of MSL, Dryer Outer Hood, Dryer Inner Hood and Dryer Interior Responses at 900 Face: ASL A:I, NISL (Red), M1:10, Outer lood (Green), M:17, Inner Hood (Blue), and M:11, Interior of Outer Hood (Pink) at EPU (converted to plant scale).

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[1:

1]

Figure 61: Comparison of MSL, Dryer Skirt Exterior, and Dryer Skirt Interior Responses at 1800 Face: MSL C:A, MSL (Red), 1:4, Skirt Exterior (Green), and M:5, Skirt Interior (Blue) at EPU (converted to plant scale)

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 8.2.2 Comparisons to Previous Data The BFN1 scale model results show some similarities to results from another scale model test and from plant scale results. The general trends are similar; however, some differences are apparent. Figures 62 through 67 are comparisons of the fluctuating pressures at outer hood locations for the QC2 plant data, QC2 SMT data, and BFN I SMT data at equivalent locations on the dryer. The BFNI SMT data shows ((

))

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 11 Figure 62: Comparison of Response at Upper Comers of Dryer Outer Hood, Red - QC2 Plant, Green - QC2 SMT, Blue - BFN1 SMT 2700 Face, Pink BFNI SMT 90° Face at EPU.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 63: Comparison of Response on Dryer Skirt, Red - QC2 Plant, Green - QC2 SMT, Blue - BFNI 2700 Face, Pink BFN1 SMT 900 Face at EPU.

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Figure 64: Comparison of Response at Lower Corners of Dryer Outer Hood, Red - QC2 Plant, Green - QC2 SIMT, Blue - BFN1 SMT 2700 Face, Pink BFNI SMT 900 Face at EPU.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP I))

Figure 65: Comparison of Response at Lower Corners of Dryer Outer Hood, Red - QC2 Plant, Green - QC2 SMT, Blue - BFN1 SMT 2700 Face, Pink BFN1 SMT 900 Face at EPU.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP i!

))

Figure 66: Comparison of Response at Inner Hood, Red - QC2 Plant, Green - QC2 SMT, Blue - BFNI SMT at EPU.

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[I Figure 67: Comparison of Rcsponse at Inner Hood, Red - QC2 Plant, Green - QC2 SMT, Blue - BFNI SMT at EPU.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 8.2.3 Flow Sweep Test Results The results from the flow sweep test illustrate the change in fluctuating pressure load on the dryer as flow (reactor power) changes. The sweep tests are performed to gather data that can describe the growth in each component of the predicted BFN I steam dryer load.

These data are used to prepare spectrograms and frequency cuts. Figures 68 and 69 are color maps or spectrograms of the flow sweep for sensors M:3 and M:9, sensors on the dryer outer hood, converted to plant scale amplitude and frequency. The z-axis of these plats is simply spectrum number, but markings are provided on the plot to indicate OLTP and EPU flow rates. As the model is operated at higher flow rates the system temperature increases, this causes the sound speed to increase and results in an increase in frequency at higher power levels. This behavior is accommodated for when the dwell test data are scaled to plant conditions because the local temperature measured at each flow rate is used to determine the frequency scaling factor. For the sweep tests and the spectrograms, used to illustrate these data, one temperature is used; therefore, a small shift in frequency is observable.

The primary (( )) signal of interest is visible slightly above ((

generally in the (( )) region. There is also another signal near

(( )) The existence of the (( )) is consistent with test predictions made prior to the BFNJ SMT using (( )) The BFNI model test data appear consistent with other model and plant data.

To understand how various components of the BFN I predicted load increase with flow rate, frequency cuts have been calculated and plotted with least squares curve fits.

Figures 70 through 75 are the frequency cuts and curve fits of the frequency bands for the dryer outer hood sensors in the following ranges:

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1. ((

2.

3.

4.

5. ))

The BFNJ model data are consistent with previous plant and SMT data [1]. The loads in the first three frequency bands generally increase proportional to flow velocity

(( )) Figures 70 through 73 show power law exponents of ((

The microphone locations shown in this report are representative of the data obtained from the other microphone locations.

Figures 74 and 75 show the frequency cuts and the curve fits for the data associated with the BFN I (( )) These plots show that the excitation from the ((

)) Figure 76 is a plot of the rms level of the ((

))

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[I 1]

Figure 68: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:3, White Dashed line is OLTP, Yellow Dashed line is EPU Page 106 of 216

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[

))

Figure 69: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:9, White Dashed line is OLTP, Yellow Dashed line is EPU Page 107 of 216

NON-PROPRIETARY VERSION G ENE-0000-0052-366 1-01-NP

((

Figure 70: Curve Fits of Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, (( )) Band Page 108 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 71: Curve Fits of Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, (( )) Band Page 109 of 216

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Figure 72: Curve Fits of Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, (( )) Band Page 110 of 216

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((

I))

Figure 73: Curve Fits of Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, (( )) Band Page 111 of 216

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Figure 74: Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, (( )) Band Page 112 of 216

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Figure 75: Curve Fits of Fluctuating Pressure Frequency Bands versus thermal power for Dryer Outer Hood, Sensor M: 1O for (( )) Band Page 113 of216

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Figure 76: Fluctuating Pressure Frequency Band versus Strouhal number for Dryer Outer Hood, Sensor M: IO for (( )) Band Page 114 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 8.2.4 Operating Pressure Shapes After processing the baseline data as discussed in Section 8.1.2.5, the crosspower spectra were used to develop a set of operating pressure shapes. These shapes are a means of visualizing the fluctuating pressure at certain frequencies. The fluctuating pressure can be visualized on the vessel because of the relatively high density of measurement locations on the vessel. Figure 77 is a plot of the summed crosspower spectra from the two datasets used to develop the operating pressure shape. The results from the second set were compared to the first set, and the points in the second set not included in the first set were simultaneously merged and shifted in frequency.

Figure 78 is an undeformed pressure shape. In the static depictions of the operating pressure shapes that follow, the red wireframe remains undeformed while the blue surfaces deform with amplitude relative to the fluctuating pressure at the frequency noted ard with direction relative to the other surfaces. Figures 79 and 80 show the most significant low frequency shape at (( )) while Figures 81 and 82 are the next highest frequency significant shape at (( )) Figures 8^ and 84 are the shape at (( )) Figures 85 and 86 are the shape at ((

)) at this condition. Note the complexity of the higher frequency shapes compared to the (( )) operating pressure shapes.

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))

Figure 77: Summed Crosspower Spectra of Whole Time Record for LIA input (Green) and Whole Time Record for ACM input (Red) at EPU.

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((

Figure 78: Undeformed Shape of Vessel. Red Wireframe Remains Undeformed.

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Figure 79: Static Depiction of (( )) Operating Pressure Shape at EPU (Note: Red Wireframe remains undeformed)

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((

1]

Figure 80: Static Depiction of (( )) Operating Pressure Shape at EPU, Opposite Phase from Previous Page 119 of 216

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Figure 81: Static Depiction of (( )) Operating Pressure Shape at EPU Page 120 of 216

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))

Figure 82: Static Depiction of (( )) Operating Pressure Shape at EPU, Opposite Phase from Previous Page 121 of 216

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Figure 83: Static Depiction of (( )) Operating Pressure Shape at EPU Page 122 of 216

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((

1]

Figure 84: Static Depiction of (( )) Operating Pressure Shape at EPU, Opposite Phase from above Page 123 of 216

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[I

))

Figure 85: Static Depiction of (( )) Operating Pressure Shape at EPU, Page 124 of 216

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[

Figure 86: Static Depiction of (( ]I Operating Pressure Shape at EPU, Opposite Phase from above Page 125 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 9.0 Uncertainty Analysis Appendix B of Reference 1, "Uncertainty of Scale Model Test Predictions," is a general uncertainty analysis for the scale model test work that applies directly to the BFNI scale model test. Based on the specific results seen during the BFNI scale model test, the frequency bands at plant scale are determined to be the same as those used in the reference:

A. [

B_

,C_.

1))

The uncertainty in scale model frequency for the BFNI SMT is the same as the uncertainty as discussed in Appendix B of Reference 1, (( )) for frequency bands A.. C and D. It is assumed that frequency band B follows this uncertainty. The similarity with the SMT benchmark data results primarily from the air temperature uncertainty, which is the same for the BFNI SMT and the QC2 SMT, and to a smaller degree from the dimensional tolerances on the boundaries that define the acoustic cavities.

The first 4 frequency bands remain consistent with the frequency bands in Reference I because the ((

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP The equation for Uncertainty in Measured Scale Model Pressures (7X,,. ncasuared is used:

11° c (1 ?L.p:r,) = \If.( ( S') + Zc (G) + (F) l o, (1)

For BFNI, rms level of scale model pressure, (Pnd, versus percentage of OLTP of all of the frequency bands appear to be fit best with a power law curve fit, 1,,,

• whereXhas the following ranges for the frequency bands:

A. [

B C.

D.

E. ))

Section 9.2.3 shows the data from which these values originate. Also, note that some of the values are from curve fits only up to ((

))

Using these values in the calculation of ly, ',,d)= x* l(I',) where 11% (V,)= 4.5%, the Measured Scale Model Pressure Uncertainty(P,,, m,,easmwred) for BFN I is:

A. [

B.

C.

D.

E.

The uncertainty levels of bands A and B are slightly less than the corresponding levels for the QC benchmark in Reference 1. The level of band C is slightly higher than that found in the SMT benchmark. The uncertainty level of band D is lower than the level for the same band in the SMT benchmark - (( ))for the BFNI SMT and (( ))

for the QC2 SMT. Section 11.3 discusses the use of uncertainty in adjusting input to the LIA.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 10.0 Data used for Load Definition This section discusses the selection of data segments to be used as input to the structural analysis and compares the results of the selection process for the input to the LIA and the A-CM. Also included is the application of frequency-specific weighting to the LIA input, and the discussion of the process and the reasoning behind the weighting.

1(1.1 Process for Selection of Segment Currently, the structural analysis process uses time domain load inputs on the dryer to predict stress. Due to the scaling discussed in Section 5.0, a 0.2 second segment of scale model test data will produce a plant scale segment approximately 2.5 seconds in length.

The current structural analysis process utilizes 2.0 to 2.5 second record lengths. The scale model data acquisition produced time records at least 30 seconds in length, so only a short portion of the 30 second record is used as input to the structural analysis process.

There is a need to determine a representative segment 0.2 seconds long from the whole 30 second long records currently being acquired during scale model testing.

The process to determine a 0.2 second segment to be extracted from the 30 second segment has several steps:

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 0

Repeated use of this process on multiple datasets of scale model and plant scale test data (plant scale data involves the selection of 2 to 2.5 second segments from time records 120 sezonds to 200 seconds long) has shown that the results from the 0.2 second segment will have the following characteristics:

• ((

10.2 Review of Results Following the process described in Section 11.1. the specific segments chosen were:

• ACM input o EPU - 11.41 to 11.61 seconds (Project: BFNlBaselineFinalO60201; Section: WithMSLMics; Run: EPUvlvAdj 1) o OLTP - 23.31 to 23.51 seconds (Project: BFNIBaselineFinal060201; Section: WithMSLMics; Run: OLTPvlvAdj 1)

• LIA input o EPU - 26.8 to 27.0 seconds (Project: BFN]BaselineFinalO60201; Section: VesselMicsOnlyGrpl; Run: EPUvlvAdj 1)

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP o OLTP -21.3 to 21.5 seconds (Project: BFNIBaselineFinaIO60201; Section: VesselMicsOnlyGrpl; Run: OLTPvlvAdj 1)

Figures 87 through 90 are comparisons of the results from the chosen segments versus results from the whole time record. As mentioned in the previous section, 11.1, the chosen segments ((

)) The results are presented in the scale model scale because both the ACM and the LIA use direct scale model results as input.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 87: LIA Input Comparison of Representative Segment (Green - 26.8 to 27.0 Seconds) - to Whole Time Record (Red) for transducer M:2 at EPU. Upper-Linear Average; Lower - Peak Hold Average Figure 88: LIA Input Comparison of Representative Segment (Green - 26.8 to 27.0 Seconds) - to Whole Time Record (Red) for transducer M:9 at EPU. Upper -

Linear Average; Lower - Peak Hold Average Page 131 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure 89: ACM Input Comparison of Representative Segment (Green - 11.41 to 11.61 Seconds) - to Whole Time Record (Red) for transducer M:3 at EPU. Upper

- Linear Average; Lower - Peak Hold Average Figure 90: ACM Input Comparison of Represeitative Segment (Grecn - 11.41 to 11.61 Seconds) - to Whole Time Record (Red) for transducer M:IO at EPU. Upper

- Linear Average; Lower - Peak Hold Average Page 132 of 216

NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01-NP Figures 91 through 94 are comparisons of the segments chosen for the LIA input and for the ACM input. Overall agreement between the two datasets is fair to good. All of the trends are present in both sets. ((

)) The noticeable frequency differences are accounted for by the different frequency scaling factors used for the different data sets and presented in Section 4.0.

Figure 95 is a comparison between results from the complete time records from which the ACM and LIA inputs were selected. When the complete time records are compared, agreement between the datasets is very good.

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))

Figure 91: ACM (Red) versus LIA (Green) Input Comparison for transducer M:7 at OLTP. Upper - Linear Average; Lower - Peak Hold Average Page 134 of 216

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))

FIigure 92: ACM1 (Red) versus LIA (Green) Input Comparison for transducer M:I 0 at OLTP. Upper - Linear Average; Lower - Peak Hold Average 1))

Figure 93: ACM1 (Red) versus LIA (Green) Input Comparison for transducer M:2 at EPU. Upper- Linear Average; Lower- Peak Hold Average Page 135 of 216

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Figure 94: ACM (Red) versus LIA (Green) Input Comparison for transducer M:9 at EPU. Upper - Linear Average; Lower - Peak Hold Average Figure 95: ACM (Red) versus LIA (Green) Input Comparison for transducer M:9 at EPU for whole record. Linear Average Results.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 10.3 BFNI SMT Load Definition Process The SMT process contains inherent uncertainties that must be considered when using SMAT data to prepare a plant specific load definition. The SMT data will be scaled using correction factors to accommodate the random and bias errors (uncertainties) associated with the current SMT process. The following correction factors are recommended for the BFNI SMT load definition:

1. Bias Error observable from SMT Benchmark report [l]

2. Testing process Random Error from the Plant Specific Scale Model Test report The fluctuating loads on the steam dryer are caused by multiple excitation mechanisms and are influenced by different resonating chambers [1]. Considering these influences, it is not acceptable to apply a single correction to the data. To accommodate the different uncertainties associated with the different components of the steam dryer loading, a set of separate correction factors for specific frequency bands are recommended.

I0.3.1 Frequency Band Specific Correction Factors Consistent with the discussions presented in the SMT Benchmark report [1], the BFNI SMAT data shall be corrected according to the four frequency bands considered to represent different content in the BWR steam dryer load. Each will be considered below.

The frequency bands are identified using the plant scale; the BFN1 frequency scaling factors must be used to convert this to BFNI SMT bands for OLTP and EPU. Section 4.0 discusses the specific scaling factors used for the BFN I SMT work.

These correction factors will be applied to the SMT time history data prior to running the LIA. The following subsections review the various frequency bands and the need for weighting in that specific band.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 10.3.1a. Frequencv Band -11 Frequency Corrections:

Random Error: ]

Bias Error: (( ]

Amplitude Corrections:

Random Error: ((

Bias Error: (( 3]

Discussion:

Reference I shows that the SMT provides an accurate frequency prediction and that the frequency uncertainty in the SMT process is very small (a few percent). The structural evaluation methodology includes additional runs in which the time increment of the input time histories has been scaled by as much as +/-10%. These runs are performed to accommodate uncertainties in the dynamic characteristics of the structure. It should be ncted that the SMT frequency uncertainty is independent of the structural frequency uncertainty. ((

From Table 9 and Figures 75-98 of the SMT Benchmark Report [Reference I] it is apparent that the SMT provides very conservative amplitude predictions in this frequency band, (( )) As shown in Reference 1,the SMT load prediction in this frequency range is very conservative. ((

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 10.3.1b. Frequency Band -II Frequency Corrections:

Random Error:

Bias Error:

Amplitude Corrections:

Random Error:

Bias Error:

Discussion:

Refer to the discussion for the (( )) frequency band above.

10.3.1c. Freguency Band 11 Frequency Corrections:

Random Error: (( 1]

Bias Error: (( h]

Arnplitude Corrections:

Random Error: [ ))

Bias Error: (( 11 Discussion:

Refer to the discussion for the (( )) frequency band above.

I 0.3.1d. 11 11 Freguencv Content (For BFNI 11 II Frequency Corrections:

Random Error: 11 11 Bias Error: R 11 Amplitude Corrections:

Random Error: U 11 Page 139 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Bias Error: (( ]I Total Correction: ((

Discussion:

Refer to the discussion provided above regarding the frequency corrections.

As discussed in Section 10.0, it is expected that the (( ))

amplitude random error will be of the same order of magnitude as observed for Quad Cities (QC). It is calculated in Section 10 to be (( )) for BFNI; therefore, a value of

(( )) is shown here. To enhance conservatism in the SMT load definition process, the random error uncertainty factor shall be used to scale the amplitude of the observed

(( )) resonances in the SMT data. The result of this scaling will be to correct the data such that the prediction provides a load definition that bounds 95% of all expected samples. The 95% confidence is a standard uncertainty reported for various instrumentation and will be retained here.

Because no BFNI plant specific data exists to extract a plant specific bias error, the worst case average bias error from the SMT Benchmark report will be considered for BFNI .

The worst case average bias error is observed to be a factor of(( )) [)). The final correction factor applied to the BFNI (( )) content will be the product of the random and bias errors: ]

1C.4 Frequency-Specific Weighting Results for LIA Segment As discussed in Section 11.3, the scale model test results to be used for input to the LIA will be weighted on a frequency-specific basis. Specifically, the (( ))

band was reduced to a level of (( f] of its original level, and the [f

)) frequency band was amplified by a factor of (( )). The frequency-specific weighting process follows:

I. ((

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 2.

3. ]

The whole time record is used so that any beginning or end effects from the filter are not present in the chosen time segment. The filter characteristic is shown in Figure 96, and the initial scale model result and the amplified scale model result are shown in Figures 97 and 99 for selected transducers. Figures 98 and 100 showtime domain comparisons for the sensor results shown in Figure 97 and 99, respectively. ((

)) The segments provided for the ACM load definition were not altered in any way. This processing is performed on the original scale model results. The LIA and ACM both scale the pressures to plant scale for application to the dryer structural analysis.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 1))

Figure 96: Filter Characteristic for Frequency Specific Weighting of Input to LIA - EPU (Red) and OLTP (Green) (Frequency Difference accounted for in Frequtenicy scaling)

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))

Figure 97: Comparison of Autopowers used as LIA Input after (Green) and before (Red) Frequency-Specific Weighting for Sensor M:2 at EPU Page 143 of 216

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Figure 98: Comparison of Time Records used as LIA Input after (Green) and before (Red) Frequency-Specific Weighting for Sensor M:2 at EPU Page 144 of 216

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((

1]

Figure 99: Comparison of Autopowers used as LIA Input after (Green) and before (Red) Frequency-Specific Weighting for Sensor M:9 at EPU Page 145 of 216

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((

Figure 100: Comparison of Time Records used as LIA Input rfter (Green) and before (Red) Frequency-Specific Weighting for Sensor M:9 at EPU Page 146 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 111.0 Discussion and Conclusions The BFNI SMT results exhibit the same general trends observed in the plant data evaluated for the SMT Benchmark as well as the previous plant SMT programs [I]. This behavior is consistent with the conclusions offered in the SMT benchmark that the BWR steam dryer normal operating fluctuating pressure loads will exhibit similar source mechanisms and characteristics. The BFNI plant specific frequencies and amplitudes are controlled by the BFNI plant configuration. Some specific conclusions are offered below:

• [

• ))

The increase in amplitude versus flow of various frequency ranges is similar to results found for other plant scale tests and other model tests as provided in Reference 1.

• ((

0]

The SMT data acquired from BFNI from this test program will be used to develop a SMT based predictive load definition for BFNI. This load definition will be applied to a Page 147 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP structural FEM to analyze the durability of the dryer structure. Two additional reports, Acoustic Finite Element model and Load Interpolation Algorithm, will be provided to describe the development of the load definition.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 12.0 References

1. Sommerville, Daniel; "General Electric Boiling Water Reactor Steam Dryer Scale Model Test Based Fluctuating Load Definition Methodology - March 2006 Benchmark Report." GE-NE-0000-0049-6652-OIP. GENE. San Jose, CA. March 2006

2. Weaver, D.S., MacLeod, G. O.,"Entrance Port Rounding Effects on Acoustic Resonance in Safety and Relief Valves". PVP Conference. 1989. Vol. 389. pg.

91- 296.

3. Rockwell, D., Naudascher, E., "Review - Self-Sustaining Oscillations of Flow Past Cavities". Transactions of the ASME, Journal of Fluids Engineering. Vol.

100., pg. 152-165 June 1978.

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NON-PROPRIETARY VERSION GENE-0000-0052-3661 NP Appendix A: Dryer Autopower Spectra at EPU - LIA Input The following plots are linear average and peak hold average plots from the complete record from which the LIA segment was selected.

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))

Figure A-I: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:1 at EPU Pagte 151 of 216

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))

Figure A-2: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:2 at EPU Figure A-3: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:3 at EPU Page 152 of 216

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((

))

Figure A-4: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:4 at EPU 1]

'Figure A-5: Pehk H0old( (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:5 at EPU Page 153 of 216

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))

Figure A-6: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:6 at EPU Figure A-7: Penk Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:7 at EPU Page 154 of 216

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((

1]

Figure A-8: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:8 at EPU

((

))

Figure A-9: IPeak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:9 at EPU Page 155 of 216

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))

Figure A-10: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M :1O at EPU

[

))

Figure A-4 1: Peak iHold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: I I at EPU Page 156 of 216

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((I Figure A-12: Penk Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: 12 at EPU

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Figure A-13: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: 13 at EPU Page 157 of 216

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((I Figure A-14: Peak Iold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: 14 at EPU

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Figure A-] 5: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: 15 at EPU Page 158 of 216

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11 Figure A-16: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M :16 at EPU\

Figure A-] 7: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: 17 at EPU Page 159 of 216

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Figure A-] 8: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: I at EPU Page 160 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Appendix B: Dryer Autopower Spectra at EPU - ACM Input Page 161 of 216

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11 Figure B-i: Penk Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M: 1 at EPU Page 162 of 216

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Figure B-2: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:2 at EPU

[I Figure B-3: Pcak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:3 at EPU Page 163 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP 11 Figure B-4: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:4 at EPU Figure B-5: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:5 at EPU Page 164 of 216

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Figure B-6: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:6 at EPU Page 165 of 216

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Figure B-7: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:7 at EPU

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Figure B-8: Peal Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:8 at EPU Page 166 of 216

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.Figure B-9: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:9 at EPU F igure B-10: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M: lO at EPU Page 167 of 216

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Figure B-I l: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M: 1I at EPU

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Figure B-12: Peak lHold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M: 12 at EPU Page 168 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure B-13: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:13 at EPU

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Figure B-14: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M: 14 at EPU Page 169 of 216

NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01-NP Figure B-15: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M: 15 at EPU I))

Figure B-16: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M: 16 at EPU Page 170 of 216

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Figure B-17: Peak lold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M: 17 at EPU

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Figure B-18: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACMI input dataset for Sensor M:I S at EPU Page 171 of 216

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Figure B-19: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLA: I at EPU Figure B-20: Peanh Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLA:2 at EPU Page 172 of 216

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Figure B-2 1: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLB:I at EPU

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Figure B-22: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor AISLB:2 at EPU Page 173 of 216

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Figure B-23: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLC: I at EPU Figure B-24: Penk Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLC:2 at EPU Page 174 of 216

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Figure B-25: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLD: I at EPU 1))

Figure :B-26: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLD:2 at EPU Page 175 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Appendix C: Dryer Autopower Spectra at OLTP - LIA Input The following plots are linear average and peakl hold average plots from the complete record from which the LIA segment was selected.

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Figure C-1: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: I at OLTP Page 177 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure C-2: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:2 at OLTP

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'Figure C-3: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:3 at OLTP Page 178 of 216

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Figure C-4: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:4 at OLTP Figure C-5: Peak 11old (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:5 at OLTP Page 179 of 216

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Figure C-6: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:6 at OLTP

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Figure C-7: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:7 at OLTP Page 180 of 216

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Figure C-8: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:8 at OLTP 1))

Figure C-9: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:9 at OLTP Page 181 of 216

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Figure C-10: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: 10 at OLTP Figure C-1I1: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: II at OLTP Page 182 of 216

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Figure C-12: Peaks Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: 12 at OLTP Figure C-13: Peak I110d (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: 14 at OLTP Page 183 of 216

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Figure C-14: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: 14 at OLTP Figure C-15: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M: 15 at OLTP Page 184 of 216

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Figure C-16: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:16 at OLTP Figure C-1 7: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:17 at OLTP Page 185 of 216

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Figure C-18: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of LIA input dataset for Sensor M:18 at OLTP Page 186 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Appendix D: Dryer Autopower Spectra at OLTP - ACM Input Page 187 of 216

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]Figure D-1: Peahk Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M: I at OLTP Page 188 of 216

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Figure D-2: Peak bold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:2 at OLTP

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Figure D-3: Penk Hbold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:3 at OLTP Page 189 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure D-4: Peak Hold (Green) and Lineal Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:4 at OLTP I]

Figure D-5: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:5 at OLTP Page 190 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure D-6: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:6 at OLTP Figure D-7: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:7 at OLTP Page 191 of 216

NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01-NP Figure D-8: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:8 at OLTP

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Figure D-9: Peal; Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:9 at OLTP Page 192 of 216

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Figure D-10: Peakklold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:1O at OLTP

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Figure D-l 1: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M: 1 I at OLTP Page 193 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661 NP Figure D-12: Peak iold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:12 at OLTP

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Figure D-13: Peak 1lold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:13 at OLTP Page 194 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661 NP Figure D-14: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:14 at OLTP

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Figure D-15: I'enk hold (Green) and liinear Average (Red) Autopowers fi-om whole time record of ACM input dataset for Sensor M: 15 at OLTP Page 195 of 216

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Figure D-16: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACMI input dataset for Sensor M: 16 at OLTP Figure D-17: Peakhold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M:17 at OLTP Page 196 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure D-18: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor M: 18 at OLTP

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Figure D-19: Pean 1Hold( (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLA: 1 at OLTP Pagte 197 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure D-20: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLA:2 at OLTP

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Figure D-21: Peak Ifoi (Green) and Liniear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLB: 1 at OLTP Page 198 of 216

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Figure D-22: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLB:2 at OLTP Figure D-23: Peanh 10old (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLC: I at OLTP Page 199 of 216

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Figure D-24: Peak Hlold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLC:2 at OLTP

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Figure D-25: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLD:1 at OLTP Page 200 of 216

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Figure D-26: Peak Hold (Green) and Linear Average (Red) Autopowers from whole time record of ACM input dataset for Sensor MSLD:2 at OLTP Page 201 of 216

NON-PROPRIETARY VERSION G ENE-0000-0052-3661-01-NP Appendix E: Dryer Autopower Spectra during Sweep Page 202 of 216

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]I Figure E-1: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M: I Page 203 of 216

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Figure E-2: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:2 Figure E-3: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:3 Page 204 of 216

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Figure E-5: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:5 Page 205 of 216

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Figure E-6: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:6 1))

Figure E-7: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:7 Page 206 of 216

NON-PROPRIETARY VERSION GENE-0000-0052-3661-01-NP Figure E-8: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:8 Figure E-9: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:9 Page 207 of 216

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Figure E-10: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M: 10 1))

Figure E-1 1: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M: 1 Page 208 of 216

NON-PROPRIETARY VERSION G ENE-0000-0052-3661-0 1-NP Figure E-12: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M: 12

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Figure E-13: Color Map of Autopowers from 61% of OLTP flow to 13 7% of OLTP flow for Sensor M:13 Page 209 of 216

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Figure E-14: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:14 1))

Figure E-15: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M: 15 Page 210 of 216

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((I Figure E-16: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M: 16 Figure E-17: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M:17 Page 211 of 216

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Figure E-18: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor M: 18

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Figure E-19: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor MSLA:I Page 212 of 216

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Figure E-20: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor MSLA:2

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Figure E-21: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor MSB: I Page 213 of 216

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Figure E-22: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for SensorMSLB:2 1))

Figure E-23: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor MSLC:1 Page 214 of 216

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Figure E-24: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor MSLC:2 Figure E-25: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor MSLD:I Page 215 of 216

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Figure E-26: Color Map of Autopowers from 61% of OLTP flow to 137% of OLTP flow for Sensor MSLD:2 Page 216 of 216